US20170084175A1 - Cloud-mediated vehicle notification exchange for localized transit events - Google Patents
Cloud-mediated vehicle notification exchange for localized transit events Download PDFInfo
- Publication number
- US20170084175A1 US20170084175A1 US15/123,005 US201515123005A US2017084175A1 US 20170084175 A1 US20170084175 A1 US 20170084175A1 US 201515123005 A US201515123005 A US 201515123005A US 2017084175 A1 US2017084175 A1 US 2017084175A1
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- vehicle
- transit
- location
- event
- notification
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Definitions
- transit events may arise that relate to a current location and/or a current route of the vehicle, such as a traffic accident; developing traffic congestion; road obstructions, such as debris or wildlife present in a lane of the road; and weather-related conditions, such as ice or flooding.
- Various techniques may be utilized to notify the user and/or adjust the autonomous control of the vehicle in response to such transit events.
- a notification of a transit event may be broadcast over a localized broadcast channel, such as a radiofrequency that encodes a voice message that can be played for the user of the message, or a digital signal that encodes a message for the device of the vehicle.
- a localized broadcast channel such as a radiofrequency that encodes a voice message that can be played for the user of the message, or a digital signal that encodes a message for the device of the vehicle.
- vehicles may locally communicate with one another using a wireless communication channel, such as localized Wi-Fi or Dedicated Short-Range Communication (DSRC) message broadcast.
- DSRC Dedicated Short-Range Communication
- a centralized service may communicate with vehicles over a long-distance channel, such as the internet, and may coordinate the delivery of notifications, such as a weather service that monitors the transit of enrolled vehicles and transmits transit-related weather information to the vehicles.
- a long-distance channel such as the internet
- localized broadcast channels are often subject to interference, crosstalk, jamming, spoofing, and interception by unintended third parties.
- vehicle-to-vehicle communication may be limited by range broadcast restrictions, and may have difficulty scaling to accommodate messaging among a large number of vehicles.
- communication mediated by a remote server may exhibit a large amount of latency, which may be problematic for the timely delivery of urgent transit event notifications; e.g., it may be difficult to provide a remote server that is capable of scaling to handle potentially millions of vehicles, and also capable of exchanging transit event notifications among such vehicles in a low-latency manner
- Such techniques involve an architecture where the transit service maintains a set of vehicle area groups, each identifying the vehicles that are associated with each location.
- the transit service may add the vehicle to the vehicle area group for the location (e.g., a vehicle area group for a portion of a geographic region that includes the reported GPS coordinate).
- the locations may be defined statically, e.g., as a set of GPS coordinates defining a boundary of a region, or dynamically, e.g., as the site of an event that impacts transit, or an area of traffic congestion.
- the transit service may identify a current or a dynamically predicted vehicle area group of the vehicle, or may create such a vehicle area group for the vehicle if one does not exist.
- the transit service may also identify the other vehicles of the vehicle area group; and may broadcast the notification to the other vehicles of the vehicle area group.
- the server may utilize a websockets architecture, wherein the devices of the respective vehicles connect to the transit service via a websocket that is maintained open and alive without having to exchange keepalive or “ping” messages.
- the server may receive transit events about a location from a vehicle of the vehicle area group for the location, and may transmit notifications of such transit events to the other vehicles of the vehicle area group via the websockets allocated for each such vehicle.
- the transit service may efficiently and rapidly exchange transit event notifications among the vehicles of the location in accordance with the techniques presented herein.
- FIG. 1 is an illustration of an example scenario featuring various techniques for broadcasting notifications about transit events for a location.
- FIG. 2 is an illustration of an example scenario featuring an architecture for broadcasting notifications about transit events for a location in accordance with the techniques presented herein.
- FIG. 3 is an illustration of an example method of broadcasting notifications about transit events for a location, in accordance with the techniques presented herein.
- FIG. 4 is an illustration of a first example system for broadcasting notifications about transit events for a location, in accordance with the techniques presented herein.
- FIG. 5 is an illustration of a second example system for broadcasting notifications about transit events for a location, in accordance with the techniques presented herein.
- FIG. 6 is an illustration of an example computer-readable medium comprising processor-executable instructions configured to embody one or more of the provisions set forth herein.
- FIG. 7 is an illustration of a first example technique for detecting transit events arising within a location, in accordance with the techniques presented herein.
- FIG. 8 is an illustration of a second example technique for detecting transit events arising within a location, in accordance with the techniques presented herein.
- FIG. 9 is an illustration of an example technique for rebroadcasting transit events arising within a location, in accordance with the techniques presented herein.
- FIG. 10 is an illustration of an example technique for broadcasting notifications of transit events to several vehicle area groups, in accordance with the techniques presented herein.
- FIG. 11 is an illustration of an example technique for notifying a user about a transit event for a location, in accordance with the techniques presented herein.
- FIG. 12 is an illustration of an example computing environment wherein one or more of the provisions set forth herein may be implemented.
- FIG. 1 is an illustration of an example scenario 100 featuring a user 102 of a vehicle 104 operated in an area 108 , such as a span of a road, alongside other vehicles 104 operated by drivers 106 .
- a transit event 110 may occur, such as a vehicular accident between two vehicles 104 , that interferes with transit in the area 108 .
- a variety of such transit events 110 may arise, such as obstructions to transit through the area 108 (e.g., the development of traffic congestion due to heavy vehicular volume, construction, or a failure of traffic signals; debris or wildlife located in a lane of the road; or weather-related events, such as flooding or the formation of ice on the road).
- Many techniques may be devised to distribute such notification of transit events 110 , some of which are illustrated in the example scenario 100 of FIG. 1 .
- information about the transit event 110 may be broadcast by a regional broadcast tower 112 using a local broadcast messaging channel, such as a selected radiofrequency over which messages may be encoded and broadcast at high power to reach a large region.
- a local broadcast messaging channel such as a selected radiofrequency over which messages may be encoded and broadcast at high power to reach a large region.
- Such messages may be distributed, e.g., as human-perceivable audio messages that are received by a radio within each vehicle 104 ; encoded text messages that are received by a device with a text display for presentation to the user 102 and drivers 106 of the vehicles 104 ; and/or encoded signals to be received and interpreted by an autonomous control system of the vehicle 104 .
- a regional broadcast service may transmit notifications 114 over a traffic message channel (TMS) of all transit events 110 occurring throughout the region including the area 108 , such as construction, vehicular accidents, and/or traffic congestion.
- TMS traffic message channel
- a first vehicle 104 may include a sensor that detects a transit event 110 such as a vehicular accident, and a vehicle-to-vehicle communication device comprising a transmitter 116 that detects the transit event 110 and transmits a notification 114 to a receiver 120 on board the vehicle 104 of the user 102 through a localized messaging channel, such as a low-broadcast radiofrequency (RF) channel, using a protocol such as Wi-Fi.
- the transmitter 120 may receive the notification 114 and utilize it in various ways, such as notifying the user 102 or adjusting an autonomous control system (e.g., reducing a cruise control speed, or engaging emergency braking). In this manner, various techniques may be utilized to exchange notifications 114 of transit events 110 to the drivers 106 of vehicles 104 and users 102 on board vehicles 104 in the area 108 .
- a regional broadcast tower 112 may broadcast a set of notifications 114 applicable throughout the region, but such broadcasting may be nonspecific, and may include information that is not applicable to some, and possibly a large proportion, of the receivers including the user 102 and other drivers 106 .
- the regional broadcast tower 112 encodes the transit event 110 for the area 108 , but also includes information about a second transit event 110 that occurs in a distant area 108 , and is likely not relevant to the user 102 or the other drivers 106 .
- the inclusion of extraneous information may desensitize the user 102 and/or other drivers 106 to the provided information, who may then miss the notification 114 of the transit event 110 that is relevant to their transit.
- the provision of the regional broadcast tower 112 to provide notifications 114 for all transit events 110 within a large region may delay the delivery of a time-sensitive notification 114 ; e.g., it may be desirable to distribute a notification 114 of the vehicular accident to the user 102 and drivers 106 of the area 108 as quickly as possible, but if the notification 114 is one of a dozen such notifications for an entire region, the delivery may be delayed and may fail to present the notification in time for the user 102 , other drivers 106 , and autonomous control systems of the vehicles 104 to react.
- the localized vehicle-to-vehicle transmission as illustrated in the second example 124 may be more localized and selective than the regional broadcast tower 112 , but its utility may be limited by a variety of factors.
- broadcast restrictions on localized broadcast messaging channels e.g., federal regulations on the maximum power of unlicensed radiofrequency transmissions
- low-power localized broadcast messaging channels may be unreliable due to a variety of factors, such as interference, crosstalk with other applications, jamming, spoofing, and/or interception by unintended individuals.
- a vehicle-to-vehicle communication system is unlikely to be effective for exchanging a large number of messages 114 among a large population of transmitters 116 (e.g., traffic congestion may feature hundreds of vehicles 104 that are attempting to transmit notifications 114 concurrently to hundreds of other vehicles 104 , and the continuous exchange of notifications 114 over the same range of localized broadcast messaging channels may severely limit the successful delivery of such notifications 114 ).
- a remote server may receive notifications 114 of transit events 110 , and may rebroadcast such notifications 114 to vehicles 114 within a particular area 108 .
- the architecture of such centralized services may affect the capabilities of such broadcast notification systems.
- a remote server may be tasked with exchanging messages 114 among millions of vehicles 104 , and may therefore incur latency in achieving such delivery, e.g, while figuring out the subset of the millions of vehicles 104 is to receive the notification 114 .
- Latency may not be a significant issue with other scenarios, such as email messages and text messages, where latency of several seconds may be acceptable and not even noticeable; however, in the context of exchanging potentially urgent messages among vehicles 104 , latency may significantly reduce the value of the transit service.
- FIG. 2 is an illustration of an example scenario 200 featuring techniques for exchanging notifications 114 of transit events 110 among the users 102 , drivers 106 , and vehicles 104 of an area 108 .
- a transit service 202 is provided that is in communication with devices aboard the vehicles 104 traveling in the area 108 , and may participate in the exchange of notifications of transit events 110 in the area 108 that affect such vehicles 104 .
- the transit service 202 associates the respective vehicles 104 within the area 108 with a particular location 204 , such as a defined span of a highway (e.g., between specified kilometer markers).
- the transit service 202 may create a vehicle area group 206 identifying the vehicles 104 that are in transit within the location 204 .
- the respective vehicles 104 may report to the transit service 202 a current location of the vehicle 104 , such as a global positioning system (GPS) coordinate, and the transit service 202 may determine the location 204 encompassing the current location of the vehicle 104 , and then add the vehicle 104 to the vehicle area group 206 for the location 204 .
- a transit event 110 may arise that is detected by a device on board a vehicle 104 , which transmits a notification 208 of the transit event 110 to the transit service 202 .
- the transit service 202 may identify the vehicle area group 206 of the vehicle 106 reporting the transit event 110 , and the other vehicles 104 of the vehicle area group 206 .
- the transit service 202 may then broadcast a notification 210 of the transit event 110 to the other vehicles 104 within the vehicle area group 206 for the location 204 .
- the transit event 110 may be relevant to a subset of the vehicles 104 communicating with the transit service 202 (e.g., vehicles 1 , 2 , and 3 , wherein vehicle 3 reports the transit event 110 to the transit service 202 ), and not relevant to other vehicles 104 that are farther away from the site of the transit event 110 , such as vehicles 4 and 5 .
- the transit service 202 may selectively broadcast the notification 210 to vehicles 1 and 2 , and may refrain from broadcasting the notification 210 to vehicle 3 (which initiated the notification 208 of the transit event 110 ) and/or vehicles 4 and 5 (which are not in the same vehicle area group 206 ).
- the transit service 110 may utilize a cloud-based architecture for broadcasting notifications 210 of transit events 110 to the vehicles 104 of the location 204 affected by the transit event 110 , and may do so by utilizing the pre-formed vehicle area group 206 that identifies such vehicles 104 , in accordance with the techniques presented herein.
- the techniques provided herein may enable a more reliable transmission of notifications 210 of transit events 110 to the vehicles 104 with the location 204 affected by the transit event 110 than localized broadcast message channels, which may be limited by such factors as range restrictions and interference.
- the techniques presented herein may utilize an internet connection of a mobile device for the exchange of notifications 210 , and internet connectivity may be both more well-developed and more ubiquitous than specialized equipment and support for a localized broadcast message channel such as traffic messaging systems (TMS).
- TMS traffic messaging systems
- the techniques provided herein may enable greater selectivity of the transmission of notifications 210 , i.e., limiting the transmission of notifications 210 to the vehicles 104 that are affected by the transit event 110 .
- selectivity may raise the signal-to-noise ratio of the notification system; may conserve the computational and messaging resources utilized in such delivery; and/or may enable faster delivery of such notifications 210 (e.g., by avoiding circumstances where the transmission of a first notification 210 that is relevant to the vehicles 104 in a particular location 204 is delayed by the transmission of a second notification 210 that does not apply to the vehicles 104 or the location 204 ).
- the techniques provided herein may scale to support a large number of vehicles 104 and/or transit events 106 , without incurring scalability penalties such as latency.
- a transit service 202 that receives a notification 208 and may utilize readily-available vehicle area groups 206 to determine the other vehicles 104 that are to receive the broadcast notification 210 may achieve such delivery faster than a transit service 202 that, ad-hoc, identifies the vehicles 104 to receive the broadcast notification 210 among a potentially large set of millions of vehicles 104 .
- Many such technical effects may arise from the broadcasting of notifications 210 of transit events 110 in accordance with the techniques presented herein.
- FIG. 3 presents a first example embodiment of the techniques presented herein, illustrated as an example method 300 of broadcasting localized transit events 110 detected during transit of a vehicle 104 .
- the example method 300 may be implemented on a device having a processor, and that is in communication with a transit service 202 having information about the locations 206 of the area 108 .
- the example method 300 may be implemented, e.g., as a set of instructions stored in a memory component of the device (e.g., a memory circuit, a platter of a hard disk drive, a solid-state memory component, or a magnetic or optical disc) that, when executed by the processor of the device, cause the device to perform the techniques presented herein.
- a memory component of the device e.g., a memory circuit, a platter of a hard disk drive, a solid-state memory component, or a magnetic or optical disc
- the example method 300 begins at 302 and involves executing 304 the instructions on the processor. Specifically, the instructions cause the device to detect 306 a location 204 of the vehicle 104 . The instructions also cause the device to transmit the location 204 to the transit service 202 to add the vehicle 104 to a vehicle area group 206 for the location 204 . The instructions also cause the device to, upon detecting a transit event 110 in the location 204 of the vehicle 104 , transmit 310 the transit event 110 to the transit service 202 for broadcasting to other vehicles 104 of the vehicle area group 206 .
- the instructions also cause the device to, upon receiving from the transit service 202 a notification 210 of a transit event 110 for the vehicle area group 206 , utilize 312 the notification 210 in the transit of the vehicle 104 .
- the example method 300 enables the vehicle 104 to participate in the exchange of notifications 210 about the transit events 110 arising within the area 108 through interaction with a travel service 202 provided in accordance with the techniques presented herein, and so ends at 314 .
- FIG. 4 presents an illustration of an example scenario 400 featuring a second example embodiment of the techniques presented herein, illustrated as an example server 402 comprising a system 410 that provides a transit service 202 to a set of vehicles 104 .
- the example system 410 may be implemented, e.g., on a server 402 having a processor 404 , a memory 408 , and a vehicle communicator 406 that communicates with the vehicles 104 .
- a portion of the server 402 and/or traffic service 202 may be located within the vehicle 104 of the user 102 , and/or may be located at a remote location.
- Respective components of the example system 410 may be implemented, e.g., as a set of instructions stored in a memory 408 of the server 402 and executable on the processor 404 of the server 402 , such that the interoperation of the components causes the server 402 to operate according to the techniques presented herein.
- the example system 410 comprises a vehicle area group manager 412 , which, upon receiving a location 204 of a vehicle 104 , adds the vehicle 104 to a vehicle area group 210 for the location 204 .
- the system 410 also comprises a transit event broadcaster 414 , which, upon receiving, from a vehicle 104 , a notification 208 of a transit event 110 for the location 204 , identifies at least one other vehicle 104 of the vehicle area group 206 , and broadcasts to the at least one other vehicle 104 of the vehicle area group 206 a notification 210 of the transit event 110 .
- the example system 410 provides a travel service 202 that facilitates the exchange of notifications 210 about the transit events 110 of the location 204 in accordance with the techniques presented herein.
- FIG. 5 presents an illustration of an example scenario 500 featuring a third example embodiment of the techniques presented herein, illustrated as an example vehicle device 502 featuring an example system 514 that enables a vehicle 104 to exchange notifications 210 with other vehicles 104 about transit events 110 arising in the location 204 of the vehicles 104 .
- the example system 514 may be implemented, e.g., on a vehicle device 502 having a processor 504 ; a memory 512 ; a location detector 506 that detects a location 204 of the vehicle 104 (e.g., a global positioning system (GPS) coordinate); a transit service communicator 508 that communicates with a transit service 202 (e.g., a wireless network adapter that is connected to the transit service 202 via an internet connection); and a transit event detector 510 that detects a transit event 110 in the location 204 of the vehicle 104 .
- GPS global positioning system
- Respective components of the example system 514 may be implemented, e.g., as a set of instructions stored in the memory 512 of the vehicle device 502 and executable on the processor 504 of the vehicle device 502 , such that the interoperation of the components causes the vehicle device 502 to operate according to the techniques presented herein.
- the example system 514 comprises a transit service interface, which transmits the location 204 of the vehicle 104 , via the transit service communicator 508 , to the transit service 202 in order to add the vehicle 104 to a vehicle area group 206 for the location 204 , and also transmits to the transit servicer 202 , via the transit service communicator 508 , a notification 208 of the transit event 110 for broadcasting to other vehicles 104 of the vehicle area group 206 .
- the example system 514 also comprises a local event notifier 518 , which, upon receiving from the transit service 202 a notification 210 of a transit event 110 for the vehicle area group 206 , utilizes the notification 210 in the transit of the vehicle 104 (e.g., by presenting the notification 210 to the user 102 ; by adjusting an autonomous control system of the vehicle 104 ; and/or by adjusting a route selected by the user 102 to reach a destination). In this manner, the example system 514 may enable the vehicle device 502 to exchange notifications 210 about the transit events 110 arising within the location 204 in accordance with the techniques presented herein.
- Still another embodiment involves a computer-readable medium comprising processor-executable instructions configured to apply the techniques presented herein.
- Such computer-readable media may include, e.g., computer-readable storage media involving a tangible device, such as a memory semiconductor (e.g., a semiconductor utilizing static random access memory (SRAM), dynamic random access memory (DRAM), and/or synchronous dynamic random access memory (SDRAM) technologies), a platter of a hard disk drive, a flash memory device, or a magnetic or optical disc (such as a CD-R, DVD-R, or floppy disc), encoding a set of computer-readable instructions that, when executed by a processor of a device, cause the device to implement the techniques presented herein.
- a memory semiconductor e.g., a semiconductor utilizing static random access memory (SRAM), dynamic random access memory (DRAM), and/or synchronous dynamic random access memory (SDRAM) technologies
- SSDRAM synchronous dynamic random access memory
- Such computer-readable media may also include (as a class of technologies that are distinct from computer-readable storage media) various types of communications media, such as a signal that may be propagated through various physical phenomena (e.g., an electromagnetic signal, a sound wave signal, or an optical signal) and in various wired scenarios (e.g., via an Ethernet or fiber optic cable) and/or wireless scenarios (e.g., a wireless local area network (WLAN) such as WiFi, a personal area network (PAN) such as Bluetooth, or a cellular or radio network), and which encodes a set of computer-readable instructions that, when executed by a processor of a device, cause the device to implement the techniques presented herein.
- WLAN wireless local area network
- PAN personal area network
- Bluetooth a cellular or radio network
- FIG. 6 An example computer-readable medium that may be devised in these ways is illustrated in FIG. 6 , wherein the implementation 600 comprises a computer-readable medium 602 (e.g., a CD-R, DVD-R, or a platter of a hard disk drive), on which is encoded computer-readable data 604 .
- This computer-readable data 604 in turn comprises a set of computer instructions 606 configured to operate according to the principles set forth herein.
- the computer instructions 606 may cause the device 610 to utilize a method of exchanging notifications 210 of transit events 110 within a location 204 with other vehicles 104 in the location 206 , such as the example method 300 of FIG. 3 .
- the computer instructions 606 may provide a system for providing a transit service 202 to a set of vehicles 104 operating in a location 204 , such as the example system 410 in the example scenario 400 of FIG. 4 .
- the computer instructions 606 may provide a system for exchanging notifications 210 of transit events 110 within a location 204 with other vehicles 104 in the location 206 , such as the example system 514 in the example scenario 500 of FIG. 5 .
- Many such computer-readable media may be devised by those of ordinary skill in the art that are configured to operate in accordance with the techniques presented herein.
- the techniques discussed herein may be devised with variations in many aspects, and some variations may present additional advantages and/or reduce disadvantages with respect to other variations of these and other techniques. Moreover, some variations may be implemented in combination, and some combinations may feature additional advantages and/or reduced disadvantages through synergistic cooperation. The variations may be incorporated in various embodiments (e.g., the example method 300 of FIG. 3 ; the example system 410 of FIG. 4 ; the example system 512 of FIG. 5 ; and the example computer-readable storage device 602 of FIG. 6 ) to confer individual and/or synergistic advantages upon such embodiments.
- a first aspect that may vary among embodiments of these techniques relates to the scenarios wherein such techniques may be utilized.
- the techniques presented herein may be used with many types of vehicles 104 , including automobiles, motorcycles, trucks, trains, buses, watercraft, aircraft, drones, and spacecraft.
- vehicles may be controlled by one or more humans, may be autonomous, or may involve a combination thereof, such as an autonomous automobile that can also be controlled by a human.
- the techniques presented herein may be utilized to provide advise users 102 of events occurring in many types of areas 108 and/or locations 202 , such as a roadway, highway, sidewalk, dirt or grass path, waterway, and airspace.
- areas 108 may also be defined statically, e.g., as the boundary of a municipality or a set of global positioning system (GPS) coordinates that define the boundaries of an area 108 , may be defined dynamically, e.g., as an area 108 where an event such as a convention is occurring, or an area 108 where traffic congestion has been detected.
- GPS global positioning system
- the techniques presented herein may be utilized to exchange notifications 210 about many types of transit events 110 occurring in an area 108 , such as vehicular accidents; the formation of traffic congestion, such as due to high vehicle volume or construction; an obstruction, such as debris or wildlife; a hazardous condition in the location 204 , such as a fire; and weather events, such as the formation of ice or flooding.
- many such variations may arise within the set of scenarios in which the techniques presented herein may be utilized.
- a second aspect that may vary among embodiments of these techniques involves the detection of the occurrence of the transit event 110 , including information about the transit event 110 that may advise the other vehicles 104 as to how to respond to the transit event 110 .
- a vehicle device may receive a report of a transit event 110 directly from the user 102 within the vehicle 104 .
- the user 102 may initiate a voice report of an observed transit event 110 , and the vehicle device may transmit the voice report of the user 102 to the transit service 202 .
- a vehicle device may evaluate telemetry of the vehicle 104 to detect a transit event 110 .
- telemetry indicating that the user 102 has engaged windshield wipers or fog lamps may indicate the presence of transit-affecting weather conditions in the location 204
- telemetry indicating an engagement of an anti-lock braking system in a particular location 204 may indicate a transit event 110 involving the formation of ice on a road surface of in the location 204
- FIG. 7 presents an illustration of an example scenario 700 featuring a third variation of this second aspect, involving a proximity sensor that generates proximity data indicating a proximity of the vehicle to a second vehicle, and a proximity data evaluator that evaluates the proximity data to identify the transit event 110 .
- a lane of a road occupied by a vehicle 104 of the user 102 is detected according to a proximity sensor 702 of the vehicle 104 .
- Such proximity sensors 702 may utilize a variety of techniques for such detection, including visual evaluation of camera data; ranging data gathered by sonar, radar, and/or lidar detection; and/or electronic communication with other vehicles 104 in the location 204 .
- the vehicle 104 is equipped with a proximity sensor 702 that detects a proximity of the vehicle 104 with respect to other vehicles 104 operating in the location 204 , such as a distance 704 between the vehicle 104 and another vehicle 104 that is ahead of and/or behind the vehicle 104 of the user 102 ; the relative speeds of the vehicles 104 ahead of and/or behind the user 102 ; and/or the rates of acceleration, braking, turning, and/or swerving by the user 102 and the drivers 106 of the other vehicles 104 .
- a proximity sensor 702 that detects a proximity of the vehicle 104 with respect to other vehicles 104 operating in the location 204 , such as a distance 704 between the vehicle 104 and another vehicle 104 that is ahead of and/or behind the vehicle 104 of the user 102 ; the relative speeds of the vehicles 104 ahead of and/or behind the user 102 ; and/or the rates of acceleration, braking, turning, and/or swerving by the user 102 and the drivers 106 of
- the proximity sensor 702 may also detect information about vehicles 104 in other lanes of the road, such as the relative or absolute speeds of vehicles 104 in adjacent lanes and/or passing in the other direction of transit, and/or whether or not such vehicles 104 are passing 706 and/or are being passed by the vehicle 104 . Moreover, such proximity data may be evaluated to detect a transit event 110 . As a first such example, the proximity sensor 702 may detect one or more vehicles 104 that are stationary in an adjacent lane, in the median of the road, and/or off to the side of the road, may indicate the occurrence of a vehicular accident and position thereof in the location 204 .
- the proximity sensor 702 may detect sudden changes in the proximity of the vehicles 104 indicating a transit event 110 , such as a rapid deceleration of a vehicle 104 behind the vehicle 104 of the user 102 that indicates a collision.
- the vehicle device 708 may utilize the proximity sensor 704 to detect such transit events 110 , and may send a notification 208 of the transit events 110 to the transit service 202 .
- FIG. 8 presents an illustration of example scenarios featuring a fourth set of variations of this second aspect, wherein a transit event 110 is detected by machine vision techniques 808 .
- a vehicle device 708 on board the vehicle 104 may include and/or be in communication with a forward-mounted camera 802 that captures a forward-facing image 804 (e.g., through a windshield 806 of the vehicle 104 ).
- a machine vision technique 808 such as an object recognition algorithm, may be applied to the image 804 , such as an object recognition technique that recognizes vehicles 104 ; extrapolates their positions within the location 204 , and/or details such as their directions, speeds, and acceleration; and, by modeling their positions, identifies that a collision has occurred.
- a second machine vision technique 808 may be applied that utilizes a line detection algorithm to detect visible lines of the road that indicate lanes, including a current lane of the vehicle 104 of the user 102 .
- the position of the vehicle 104 on the road may therefore be extrapolated by the machine vision technique 808 , and this information may be utilized to provide additional information about the transit event 110 (e.g., which lane(s) the transit event 110 affects) and/or to adjust the navigation of the vehicle 104 and/or advise the user 102 (e.g., determining whether the current lane of the vehicle 104 avoids or is obstructed by the transit event 110 ).
- machine vision techniques may be applied to the image 804 to about the transit event 110 , such as object recognition to detect and optionally count a number of visible vehicles 104 ahead of the vehicle 104 of the user 102 in the respective lanes as a measurement of traffic congestion, and/or visual sizing machine vision techniques that estimate a distance of vehicles 104 ahead of the vehicle 104 of the user 102 .
- a downward-facing camera 802 may capture a downward-facing image 804 of the location 204 ; an object recognition algorithm may be applied to detect objects that are visible on the surface of the road and that may indicate a transit event 110 , such as ice, water, debris, or potholes; and a line detection machine vision technique 808 may be utilized to detect the visible lines indicating the lanes of the road, and/or the current lane that is currently occupied by the vehicle 104 of the user 102 . Many such techniques may be utilized to detect and describe transit events 110 occurring within the location 204 of the vehicle 104 for reporting to the transit service 202 in accordance with the techniques presented herein.
- a third aspect that may vary among embodiments of the techniques presented herein involves the manner of exchanging notifications 210 of transit events 110 among the vehicles 104 and the transit service 202 .
- vehicle devices and travel service 202 may communicate through a wide range of communication channels, such as electromagnetic wave transmissions at various frequencies.
- Such communication channels may also be utilized to exchange notifications 210 encoded in various ways, such as a human-receivable voice or tone; a human-readable message, such as text, images, and/or video; encoded data that describes the transit event 110 , such as an extensible markup language (XML) providing fields that identify properties of the transit event 110 such as its precise location, type, and severity; and/or encoded data that provides instructions for autonomous control of a vehicle navigation system, such as instructions to engage a braking system to slow or halt the vehicle 104 , and/or instructions to re-route the transit of the vehicle 104 through an alternative area.
- XML extensible markup language
- a vehicle communicator 406 of a server 402 providing the travel service 202 may comprise an internet connection that communicates with vehicle devices through the internet using a websocket protocol.
- a vehicle area group manager 412 may, in addition to adding a vehicle 104 to a vehicle area group 206 , allocate a websocket to communicate with the vehicle 104 through the internet using the websocket protocol; and the transit event broadcaster 414 may broadcast the notification of the transit event 110 to the respective vehicles 104 through the respective websockets.
- the transit service communicator 508 of a vehicle 104 may further comprise an internet connection through which the transit service communicator 508 communicates with the transit service 202 using a websocket protocol, and the local event notifier 518 may receive the notification 210 of the transit event 110 from the transit service 202 through a websocket of the websocket protocol that has been allocated to communicate with the transit service 202 .
- a protocol such as websockets may enable further advantages, such as a reduced reliance on ping or keepalive messages to maintain the communication channel; as a result, the communication resources (e.g., radiofrequency bandwidth) may be conserved for the actual exchange of notifications 210 of transit events 110 , which may also reduce the latency in the delivery of such notifications 210 , and the scalability to support broadcasting to a large number of vehicles 104 in a particular location 204 with reduced interference.
- Websockets may also be advantageous due to the greater incidence of interruption of connectivity of vehicles 104 in transit, since ephemeral lapses in connectivity may not necessitate the exchange of network communication, but may be tolerated as part of the transit service 202 .
- a transit service 202 may, upon receiving from the vehicle a first location 204 , determine whether a vehicle area group 206 exists for the first location 204 , and upon determining that a vehicle area group 206 does not exist for the first location 204 , create a vehicle area group 206 for the first location 204 .
- the transit service 202 may also, upon receiving from the vehicle 104 a second location 204 of the vehicle 204 (e.g., an updated global positioning service (GPS) coordinate), determine whether the second location 204 is also associated with the vehicle area group 206 ; and upon determining that the second location 204 is not associated with the vehicle area group 206 , remove the vehicle 104 from the vehicle area group 206 for the first location 204 (e.g., transferring the association of the vehicle 104 from the first vehicle area group 206 for the first location 204 to a second vehicle area group 206 for the second location 204 ).
- GPS global positioning service
- FIG. 9 presents an illustration of an example scenario 900 featuring a third set of variations of this third aspect involving the broadcasting of various notifications 208 of transit events 110 for a location 204 .
- the transit service 202 may be utilized to retransmit notifications 208 generated by other services, and vice versa.
- a vehicle device 706 may further comprise a local transit event rebroadcaster that locally rebroadcasts the notification 206 of the transit event 110 over a localized broadcast messaging channel.
- a vehicle device 2706 may utilize a transmitter 116 broadcast the notification 208 using a local broadcast messaging channel, such as a local, low-power radiofrequency (RF) broadcast, or a directed vehicle-to-vehicle communication channel.
- RF radiofrequency
- a receiver 120 within a second vehicle 104 that is not enrolled in the transit service 202 , and/or that is enrolled but that is not in communication with the transit service 202 due to a temporary communication interruption, may therefore receive the local broadcast.
- a localized broadcast channel monitor may be utilized to monitor a localized broadcast messaging channel, such as broadcasts by a regional broadcast tower 112 (e.g., a traffic message channel (TMS) broadcaster), and may retransmit notifications 210 of transit events 110 received through such a localized broadcast messaging channel to the transit service 202 for rebroadcasting to the other vehicles 104 of the vehicle area group 206 for the location 204 involved in the transit event 110 .
- the transit service may remotely monitor sources of information about transit events 110 , such as traffic message channel (TMS) information provided over the internet, and may broadcast notifications 210 of transit events 110 according to the vehicle area groups 206 for the locations 204 involved in the transit events 110 .
- TMS traffic message channel
- Such broadcasting may enable delivery of the localized broadcast message to other vehicles 104 that are not monitoring the localized broadcast messaging channel, but that are in communication with the transit service 202 .
- the transit service 202 and/or the vehicle device 706 may also provide information to other services for transmission via localized broadcast messaging channels. For example, upon receiving a notification 208 from a vehicle 104 in a location 204 of a transit event 110 , the transit service 202 may, in addition to broadcasting a notification 210 to the vehicles 104 of the vehicle area group 206 , transmit the notification 210 to the regional broadcast tower 112 for regional rebroadcast. Alternatively, the vehicle device 706 may transmit the notification 208 to the to the regional broadcast tower 112 for regional rebroadcast.
- Such rebroadcasting techniques may coordinate the exchange of notifications 210 among the vehicles 104 enrolled in the transit service 202 with the exchange of notifications 210 among other vehicles 104 that are not enrolled in the transit service 202 , and/or that have lost communication with the transit service 202 .
- FIG. 10 presents an illustration of an example scenario 1000 featuring further variations of this third aspect involving the broadcasting of various notifications 208 of transit events 110 for various locations 204 .
- the transit service 202 may also determine other recipients of the information to which the notification 210 of the transit event 110 may apply.
- the transit service 202 receives a notification 208 of a multi-vehicle accident in a particular location 204 , and, in addition to identifying the vehicles 104 within the vehicle area group 206 for the third location 204 , may evaluate a second location 204 that may also be affected by the transit event 110 , such as a distant stretch of the road that approaches the site of the transit event 110 ; an entrance ramp of a nearby road that leads to the transit event 110 ; or a second road that passes over or under the site of the transit event 110 .
- the transit service 202 may determine whether the transit event 110 applies to the vehicles 104 of the second location 204 , and may broadcast the notification 210 to the vehicles 104 in the vehicle area group 206 of the second location 204 .
- a weather-related event that is detected in a first location 204 may be projected as following a weather pattern (such as a wind direction) that is likely to affect a second location 204 , and the transit service 202 may broadcast the notification 210 to the vehicles 104 in the vehicle area group 206 for the second location 204 .
- the notification 210 may be updated to reflect a recommendation to the vehicles 104 , including the user 104 and the other drivers 106 , as to how to respond to the transit event 110 .
- the second location 204 features a detour option 1002 for avoiding the location of the transit event 110 , such as an exit ramp, an alternate route, or a second lane of a road that is not affected by the transit event 110 that impacts a first lane of the road.
- the transit service 220 may therefore add, to the notification 210 broadcast to the vehicles 104 of the vehicle area group 206 , a recommendation 1004 to take the detour option 1002 to avoid the location 204 of the transit event 110 .
- the transit service 202 may be configured to notify first responders as to the occurrence of a transit event 110 , where such first responders provide a first response service relating to the transit event 110 for the location 204 .
- the transit service 202 may evaluate the information about the transit event 110 and may determine whether police, fire control personnel, medical personnel, tow trucks, or mechanics are to be directed to the location 204 of the transit event 110 .
- the transit service 202 may therefore generate a notification 1006 to the first responders 1008 , and may transmit the notification 1006 of the transit event 110 to the first responders 1008 .
- the transit service 202 may comprise a transit event verifier that endeavors to verify the transit events 110 reported by respective vehicles 104 .
- a transit event 110 involving a sudden braking incident by a vehicle 104 may indicate a transit event 110 such as an accident or ice, for which a notification 210 of the transit event 110 is to broadcast.
- the sudden braking may also indicate a transient event, such as a brief encounter with wildlife, or a vehicle or driver error, such as accidentally activating the brakes or misperceiving the presence of a vehicle in a nearby lane.
- the transit service 202 may endeavor to verify the transit event 110 by identifying a second vehicle 104 of the vehicle area group 206 that is capable of verifying the transit event 110 , and transmitting to the second vehicle 104 a request to verify the transit event 110 (e.g., by asking the driver 106 of the second vehicle 104 to confirm or refute the transit event 110 , and/or by utilizing sensors of the second vehicle 104 ).
- the broadcasting of the notification 210 may be contingent upon first receiving a verification of the transit event 110 from the second vehicle 104 .
- the transit service 202 may utilize various techniques to anonymize the vehicle 104 that transmitted the notification 208 of the the transit event 110 .
- the transit service 202 may extrapolate the GPS coordinate transmitted by the vehicle 104 to the GPS coordinate of the transit event 110 , and may include the latter GPS coordinate but not the former GPS coordinate that identifies which vehicle 104 transmitted the transit event 110 .
- the transit service 202 may remove identifying features of such media before broadcast to the other vehicles 104 of the vehicle area group 206 .
- Many such techniques may be included in the exchange of notifications 210 of transit events 110 in accordance with the techniques presented herein.
- a fifth aspect that may vary among embodiments of the techniques presented herein involves the manner of utilizing a transit event during the transit of the vehicle 104 , such as advising a user 102 of the occurrence and details of a transit event 110 .
- information about the transit event 110 may be described to the user 102 in a variety of ways.
- the transit event 110 may be described in absolute terms (e.g., “warning: accident at northbound 14 kilometer mark”) or in relative terms (e.g., “warning: accident one kilometer ahead”), and may include a recommendation to the use 102 to adjust the control of the vehicle 104 (e.g., “reduce speed by 10 kph” or “engage fog lamps”).
- the device 202 may or may not explain the basis of a recommendation responsive to the transit event 110 , e.g., why the user 102 is advised to choose an alternate route or lane of a road.
- a vehicle device 708 may either present the recommendation (e.g., “recommendation: maintain current lane”), or may defer such recommendation until detecting that the user 102 is considering transitioning to a different lane (e.g., upon detecting the user's activation of a turn signal).
- the transit of the vehicle 104 may be controlled by a vehicle control system according to a driving behavior profile, and the transit event 110 may prompt the vehicle 104 to the driving behavior profile of the vehicle control system in response to the transit event 110 (e.g., reducing a cruise-control speed of the vehicle 104 , engaging a braking system, and/or adjusting a route for the transit of the vehicle 104 to choose an alternative route that avoids the transit event 110 ).
- the transit event 110 may prompt the vehicle 104 to the driving behavior profile of the vehicle control system in response to the transit event 110 (e.g., reducing a cruise-control speed of the vehicle 104 , engaging a braking system, and/or adjusting a route for the transit of the vehicle 104 to choose an alternative route that avoids the transit event 110 ).
- FIG. 11 presents an illustration of a set of exemplary scenarios 1100 whereby a vehicle device 708 may notify the user 102 about a transit event 110 .
- a visual and/or audial indicator may be presented to the user 102 by the vehicle device 708 and/or vehicle 104 , such as a light on the dashboard of the vehicle 104 or an audio or voice cue 1104 prompting the user to select a particular lane 1112 to avoid the transit event 110 .
- a visual indicator 1110 may be presented on a window 1108 of the vehicle 104 , and, optionally, may be presented at a selected location 1114 on the window 1108 that correlates the visual indicator 1110 with the location 1112 of the transit event 110 through the window 1108 from the perspective of the user 102 (e.g., presenting a visual arrow and/or highlighting the location of the transit event 110 when viewed through the window 1108 by the user 102 ).
- the user 102 may wear one or more wearable devices while operating the vehicle 104 , such as a pair of eyeglasses 1116 or a wristwatch 1118 .
- the presentation of the notification 210 of the transit event 110 may be achieved through such wearable devices, e.g., by presenting a visual indicator 1120 within the viewable region of the eyeglasses 1116 worn by the user 102 , and/or issuing a vibration alert 1122 through the wristwatch 1118 of the user 102 to indicate the location of the transit event 110 (e.g., flashing a leftward visual indicator 1120 or a vibration alert 1122 on the user's left wrist to draw the user's attention to the left lane where a transit event 110 has occurred).
- Many such techniques may be utilized to present to the user 102 the notification 210 of the transit event 110 in accordance with the techniques presented herein.
- FIG. 12 and the following discussion provide a brief, general description of a suitable computing environment to implement embodiments of one or more of the provisions set forth herein.
- the operating environment of FIG. 12 is only one example of a suitable operating environment and is not intended to suggest any limitation as to the scope of use or functionality of the operating environment.
- Example computing devices include, but are not limited to, personal computers, server computers, hand-held or laptop devices, mobile devices (such as mobile phones, Personal Digital Assistants (PDAs), media players, and the like), multiprocessor systems, consumer electronics, mini computers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
- Computer readable instructions may be distributed via computer readable media (discussed below).
- Computer readable instructions may be implemented as program modules, such as functions, objects, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types.
- APIs Application Programming Interfaces
- the functionality of the computer readable instructions may be combined or distributed as desired in various environments.
- FIG. 12 illustrates an example of a system 1200 comprising a computing device 1202 configured to implement one or more embodiments provided herein.
- computing device 1202 includes at least one processing unit 1206 and memory 1208 .
- memory 1208 may be volatile (such as RAM, for example), non-volatile (such as ROM, flash memory, etc., for example) or some combination of the two. This configuration is illustrated in FIG. 12 by dashed line 1204 .
- device 1202 may include additional features and/or functionality.
- device 1202 may also include additional storage (e.g., removable and/or non-removable) including, but not limited to, magnetic storage, optical storage, and the like.
- additional storage is illustrated in FIG. 12 by storage 1210 .
- computer readable instructions to implement one or more embodiments provided herein may be in storage 1210 .
- Storage 1210 may also store other computer readable instructions to implement an operating system, an application program, and the like.
- Computer readable instructions may be loaded in memory 1208 for execution by processing unit 1206 , for example.
- Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions or other data.
- Memory 1208 and storage 1210 are examples of computer storage media.
- Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by device 1202 . Any such computer storage media may be part of device 1202 .
- Device 1202 may also include communication connection(s) 1216 that allows device 1202 to communicate with other devices.
- Communication connection(s) 1216 may include, but is not limited to, a modem, a Network Interface Card (NIC), an integrated network interface, a radio frequency transmitter/receiver, an infrared port, a USB connection, or other interfaces for connecting computing device 1202 to other computing devices.
- Communication connection(s) 1216 may include a wired connection or a wireless connection. Communication connection(s) 1216 may transmit and/or receive communication media.
- Computer readable media may include communication media.
- Communication media typically embodies computer readable instructions or other data in a “modulated data signal” such as a carrier wave or other transport mechanism and includes any information delivery media.
- modulated data signal may include a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal.
- Device 1202 may include input device(s) 1214 such as keyboard, mouse, pen, voice input device, touch input device, infrared cameras, video input devices, and/or any other input device.
- Output device(s) 1212 such as one or more displays, speakers, printers, and/or any other output device may also be included in device 1202 .
- Input device(s) 1214 and output device(s) 1212 may be connected to device 1202 via a wired connection, wireless connection, or any combination thereof.
- an input device or an output device from another computing device may be used as input device(s) 1214 or output device(s) 1212 for computing device 1202 .
- Components of computing device 1202 may be connected by various interconnects, such as a bus.
- Such interconnects may include a Peripheral Component Interconnect (PCI), such as PCI Express, a Universal Serial Bus (USB), firewire (IEEE 1394), an optical bus structure, and the like.
- PCI Peripheral Component Interconnect
- USB Universal Serial Bus
- IEEE 1394 Firewire
- optical bus structure an optical bus structure, and the like.
- components of computing device 1202 may be interconnected by a network.
- memory 1208 may be comprised of multiple physical memory units located in different physical locations interconnected by a network.
- a computing device 1220 accessible via network 1218 may store computer readable instructions to implement one or more embodiments provided herein.
- Computing device 1202 may access computing device 1220 and download a part or all of the computer readable instructions for execution.
- computing device 1202 may download pieces of the computer readable instructions, as needed, or some instructions may be executed at computing device 1202 and some at computing device 1220 .
- a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer.
- an application running on a controller and the controller can be a component.
- One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers.
- the claimed subject matter may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter.
- article of manufacture as used herein is intended to encompass a computer program accessible from any computer-readable device, carrier, or media.
- one or more of the operations described may constitute computer readable instructions stored on one or more computer readable media, which if executed by a computing device, will cause the computing device to perform the operations described.
- the order in which some or all of the operations are described should not be construed as to imply that these operations are necessarily order dependent. Alternative ordering will be appreciated by one skilled in the art having the benefit of this description. Further, it will be understood that not all operations are necessarily present in each embodiment provided herein.
- the word “example” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “example” is not necessarily to be construed as advantageous over other aspects or designs. Rather, use of the word example is intended to present concepts in a concrete fashion.
- the term “or ” is intended to mean an inclusive “or ” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X employs A or B” is intended to mean any of the natural inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, then “X employs A or B” is satisfied under any of the foregoing instances.
- the articles “a” and “an ” as used in this application and the appended claims may generally be construed to mean one or more unless specified otherwise or clear from context to be directed to a singular form.
Abstract
Vehicles in transit within a location may transmit and/or receive information about transit events arising within the location, such as accidents, developing weather, and road obstructions. Because localized exchange channels, such as a radiofrequency broadcast, may be range-limited and/or unreliable, a centralized service may be provided to facilitate the exchange of notifications about transit events, but it may be difficult to provide a centralized service that is both scalable to millions of vehicles and capable of low-latency exchange of time-sensitive notifications for transit events. The techniques presented herein provide an architecture for broadcasting transit events through a transit service that maintains vehicle area groups, respectively identifying the vehicles that are associated with each location. The service may receive a notification of a transit event for a location, and may utilize the vehicle area group for the location to broadcast the notification to the other vehicles of the area group.
Description
- The present application claims priority under 35 U.S.C. §119(e) to U.S. Patent Application No. 61/946,962, filed on Mar. 3, 2014, the entirety of which is incorporated by reference as if fully rewritten herein.
- Within the field of computing, many scenarios involve devices that inform and assist a user within a vehicle, e.g., by autonomously navigating the vehicle, and/or presenting transit-related information to a driver of the vehicle. In such scenarios, transit events may arise that relate to a current location and/or a current route of the vehicle, such as a traffic accident; developing traffic congestion; road obstructions, such as debris or wildlife present in a lane of the road; and weather-related conditions, such as ice or flooding. Various techniques may be utilized to notify the user and/or adjust the autonomous control of the vehicle in response to such transit events.
- This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key factors or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
- Many techniques may be utilized to exchange messages about transit events, such as events that may be related to or have an impact on a roadway network of a city. As a first such example, a notification of a transit event may be broadcast over a localized broadcast channel, such as a radiofrequency that encodes a voice message that can be played for the user of the message, or a digital signal that encodes a message for the device of the vehicle. As a second such example, vehicles may locally communicate with one another using a wireless communication channel, such as localized Wi-Fi or Dedicated Short-Range Communication (DSRC) message broadcast. As a third such example, a centralized service may communicate with vehicles over a long-distance channel, such as the internet, and may coordinate the delivery of notifications, such as a weather service that monitors the transit of enrolled vehicles and transmits transit-related weather information to the vehicles.
- While many such techniques may be devised, several considerations of such techniques may limit the utility of such techniques. As a first such example, localized broadcast channels are often subject to interference, crosstalk, jamming, spoofing, and interception by unintended third parties. As a second such example, vehicle-to-vehicle communication may be limited by range broadcast restrictions, and may have difficulty scaling to accommodate messaging among a large number of vehicles. As a third such example, communication mediated by a remote server may exhibit a large amount of latency, which may be problematic for the timely delivery of urgent transit event notifications; e.g., it may be difficult to provide a remote server that is capable of scaling to handle potentially millions of vehicles, and also capable of exchanging transit event notifications among such vehicles in a low-latency manner
- Presented herein are techniques for exchanging notifications of transit events among vehicle using a transit service. Such techniques involve an architecture where the transit service maintains a set of vehicle area groups, each identifying the vehicles that are associated with each location. When a vehicle reports a particular location (e.g., a set of global positioning service (GPS) coordinates), the transit service may add the vehicle to the vehicle area group for the location (e.g., a vehicle area group for a portion of a geographic region that includes the reported GPS coordinate). The locations may be defined statically, e.g., as a set of GPS coordinates defining a boundary of a region, or dynamically, e.g., as the site of an event that impacts transit, or an area of traffic congestion. When the transit service receives a notification of a transit event from a vehicle within a particular location, the transit service may identify a current or a dynamically predicted vehicle area group of the vehicle, or may create such a vehicle area group for the vehicle if one does not exist. The transit service may also identify the other vehicles of the vehicle area group; and may broadcast the notification to the other vehicles of the vehicle area group. As one such example, the server may utilize a websockets architecture, wherein the devices of the respective vehicles connect to the transit service via a websocket that is maintained open and alive without having to exchange keepalive or “ping” messages. The server may receive transit events about a location from a vehicle of the vehicle area group for the location, and may transmit notifications of such transit events to the other vehicles of the vehicle area group via the websockets allocated for each such vehicle. In this manner, the transit service may efficiently and rapidly exchange transit event notifications among the vehicles of the location in accordance with the techniques presented herein.
- To the accomplishment of the foregoing and related ends, the following description and annexed drawings set forth certain illustrative aspects and implementations. These are indicative of but a few of the various ways in which one or more aspects may be employed. Other aspects, advantages, and novel features of the disclosure will become apparent from the following detailed description when considered in conjunction with the annexed drawings.
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FIG. 1 is an illustration of an example scenario featuring various techniques for broadcasting notifications about transit events for a location. -
FIG. 2 is an illustration of an example scenario featuring an architecture for broadcasting notifications about transit events for a location in accordance with the techniques presented herein. -
FIG. 3 is an illustration of an example method of broadcasting notifications about transit events for a location, in accordance with the techniques presented herein. -
FIG. 4 is an illustration of a first example system for broadcasting notifications about transit events for a location, in accordance with the techniques presented herein. -
FIG. 5 is an illustration of a second example system for broadcasting notifications about transit events for a location, in accordance with the techniques presented herein. -
FIG. 6 is an illustration of an example computer-readable medium comprising processor-executable instructions configured to embody one or more of the provisions set forth herein. -
FIG. 7 is an illustration of a first example technique for detecting transit events arising within a location, in accordance with the techniques presented herein. -
FIG. 8 is an illustration of a second example technique for detecting transit events arising within a location, in accordance with the techniques presented herein. -
FIG. 9 is an illustration of an example technique for rebroadcasting transit events arising within a location, in accordance with the techniques presented herein. -
FIG. 10 is an illustration of an example technique for broadcasting notifications of transit events to several vehicle area groups, in accordance with the techniques presented herein. -
FIG. 11 is an illustration of an example technique for notifying a user about a transit event for a location, in accordance with the techniques presented herein. -
FIG. 12 is an illustration of an example computing environment wherein one or more of the provisions set forth herein may be implemented. - The claimed subject matter is now described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the claimed subject matter. It may be evident, however, that the claimed subject matter may be practiced without these specific details. In other instances, structures and devices are shown in block diagram form in order to facilitate describing the claimed subject matter.
- A. Introduction
-
FIG. 1 is an illustration of anexample scenario 100 featuring auser 102 of avehicle 104 operated in anarea 108, such as a span of a road, alongsideother vehicles 104 operated bydrivers 106. In thisexample scenario 100, atransit event 110 may occur, such as a vehicular accident between twovehicles 104, that interferes with transit in thearea 108. A variety ofsuch transit events 110 may arise, such as obstructions to transit through the area 108 (e.g., the development of traffic congestion due to heavy vehicular volume, construction, or a failure of traffic signals; debris or wildlife located in a lane of the road; or weather-related events, such as flooding or the formation of ice on the road). - It may be desirable to transmit a notification of the
transit events 110 to theuser 102 and theother drivers 106 ofsuch vehicles 104, as such notification may alert them to thetransit event 110 as a safety precaution, and/or enable theuser 102 andother drivers 106 to choose an alternate route that avoids thearea 108. Many techniques may be devised to distribute such notification oftransit events 110, some of which are illustrated in theexample scenario 100 ofFIG. 1 . - As a first such example 122, information about the
transit event 110 may be broadcast by aregional broadcast tower 112 using a local broadcast messaging channel, such as a selected radiofrequency over which messages may be encoded and broadcast at high power to reach a large region. Such messages may be distributed, e.g., as human-perceivable audio messages that are received by a radio within eachvehicle 104; encoded text messages that are received by a device with a text display for presentation to theuser 102 anddrivers 106 of thevehicles 104; and/or encoded signals to be received and interpreted by an autonomous control system of thevehicle 104. For example, a regional broadcast service may transmitnotifications 114 over a traffic message channel (TMS) of alltransit events 110 occurring throughout the region including thearea 108, such as construction, vehicular accidents, and/or traffic congestion. - As a second such example 124, a
first vehicle 104 may include a sensor that detects atransit event 110 such as a vehicular accident, and a vehicle-to-vehicle communication device comprising atransmitter 116 that detects thetransit event 110 and transmits anotification 114 to areceiver 120 on board thevehicle 104 of theuser 102 through a localized messaging channel, such as a low-broadcast radiofrequency (RF) channel, using a protocol such as Wi-Fi. Thetransmitter 120 may receive thenotification 114 and utilize it in various ways, such as notifying theuser 102 or adjusting an autonomous control system (e.g., reducing a cruise control speed, or engaging emergency braking). In this manner, various techniques may be utilized to exchangenotifications 114 oftransit events 110 to thedrivers 106 ofvehicles 104 andusers 102 onboard vehicles 104 in thearea 108. - However, some disadvantages may arise within such techniques that affect the distribution of
such notifications 114. - As a first such example, a
regional broadcast tower 112 may broadcast a set ofnotifications 114 applicable throughout the region, but such broadcasting may be nonspecific, and may include information that is not applicable to some, and possibly a large proportion, of the receivers including theuser 102 andother drivers 106. For example, in the first example 122 ofFIG. 1 , theregional broadcast tower 112 encodes thetransit event 110 for thearea 108, but also includes information about asecond transit event 110 that occurs in adistant area 108, and is likely not relevant to theuser 102 or theother drivers 106. The inclusion of extraneous information may desensitize theuser 102 and/orother drivers 106 to the provided information, who may then miss thenotification 114 of thetransit event 110 that is relevant to their transit. Moreover, the provision of theregional broadcast tower 112 to providenotifications 114 for alltransit events 110 within a large region may delay the delivery of a time-sensitive notification 114; e.g., it may be desirable to distribute anotification 114 of the vehicular accident to theuser 102 anddrivers 106 of thearea 108 as quickly as possible, but if thenotification 114 is one of a dozen such notifications for an entire region, the delivery may be delayed and may fail to present the notification in time for theuser 102,other drivers 106, and autonomous control systems of thevehicles 104 to react. - As a second such example, the localized vehicle-to-vehicle transmission as illustrated in the second example 124 may be more localized and selective than the
regional broadcast tower 112, but its utility may be limited by a variety of factors. For example, broadcast restrictions on localized broadcast messaging channels (e.g., federal regulations on the maximum power of unlicensed radiofrequency transmissions) may reduce the power and range with which thetransmitter 116 may transmit thenotification 114, causingvehicles 104 that are outside of the range of the low-poweredtransmitter 116 not to receive thenotification 114. For example, in a high-speed environment such as a highway, it may be desirable to transmit thenotification 114 tovehicles 104 over a hundred meters away, but thetransmitter 116 may have a restricted range of twenty meters. Moreover, low-power localized broadcast messaging channels may be unreliable due to a variety of factors, such as interference, crosstalk with other applications, jamming, spoofing, and/or interception by unintended individuals. For example a vehicle-to-vehicle communication system is unlikely to be effective for exchanging a large number ofmessages 114 among a large population of transmitters 116 (e.g., traffic congestion may feature hundreds ofvehicles 104 that are attempting to transmitnotifications 114 concurrently to hundreds ofother vehicles 104, and the continuous exchange ofnotifications 114 over the same range of localized broadcast messaging channels may severely limit the successful delivery of such notifications 114). - Due to these difficulties with localized exchange of
notifications 114, other techniques may be utilized. For example, a remote server may receivenotifications 114 oftransit events 110, and may rebroadcastsuch notifications 114 tovehicles 114 within aparticular area 108. However, the architecture of such centralized services may affect the capabilities of such broadcast notification systems. In particular, a remote server may be tasked with exchangingmessages 114 among millions ofvehicles 104, and may therefore incur latency in achieving such delivery, e.g, while figuring out the subset of the millions ofvehicles 104 is to receive thenotification 114. Such latency may not be a significant issue with other scenarios, such as email messages and text messages, where latency of several seconds may be acceptable and not even noticeable; however, in the context of exchanging potentially urgent messages amongvehicles 104, latency may significantly reduce the value of the transit service. These and other complications may arise within various techniques for distributingnotifications 114 among thevehicles 104 of alocation 102. - B. Presented Techniques
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FIG. 2 is an illustration of anexample scenario 200 featuring techniques for exchangingnotifications 114 oftransit events 110 among theusers 102,drivers 106, andvehicles 104 of anarea 108. - In this
example scenario 200, atransit service 202 is provided that is in communication with devices aboard thevehicles 104 traveling in thearea 108, and may participate in the exchange of notifications oftransit events 110 in thearea 108 that affectsuch vehicles 104. In particular, thetransit service 202 associates therespective vehicles 104 within thearea 108 with aparticular location 204, such as a defined span of a highway (e.g., between specified kilometer markers). For therespective locations 204, thetransit service 202 may create avehicle area group 206 identifying thevehicles 104 that are in transit within thelocation 204. For example, therespective vehicles 104 may report to the transit service 202 a current location of thevehicle 104, such as a global positioning system (GPS) coordinate, and thetransit service 202 may determine thelocation 204 encompassing the current location of thevehicle 104, and then add thevehicle 104 to thevehicle area group 206 for thelocation 204. Atransit event 110 may arise that is detected by a device on board avehicle 104, which transmits anotification 208 of thetransit event 110 to thetransit service 202. Thetransit service 202 may identify thevehicle area group 206 of thevehicle 106 reporting thetransit event 110, and theother vehicles 104 of thevehicle area group 206. Thetransit service 202 may then broadcast anotification 210 of thetransit event 110 to theother vehicles 104 within thevehicle area group 206 for thelocation 204. For example, in theexample scenario 200 ofFIG. 2 , thetransit event 110 may be relevant to a subset of thevehicles 104 communicating with the transit service 202 (e.g.,vehicles vehicle 3 reports thetransit event 110 to the transit service 202), and not relevant toother vehicles 104 that are farther away from the site of thetransit event 110, such asvehicles transit service 202 may selectively broadcast thenotification 210 tovehicles notification 210 to vehicle 3 (which initiated thenotification 208 of the transit event 110) and/orvehicles 4 and 5 (which are not in the same vehicle area group 206). In this manner, thetransit service 110 may utilize a cloud-based architecture forbroadcasting notifications 210 oftransit events 110 to thevehicles 104 of thelocation 204 affected by thetransit event 110, and may do so by utilizing the pre-formedvehicle area group 206 that identifiessuch vehicles 104, in accordance with the techniques presented herein. - C. Technical Effects
- The techniques presented herein may provide a variety of technical effects in the scenarios provided herein.
- As a first such example, the techniques provided herein may enable a more reliable transmission of
notifications 210 oftransit events 110 to thevehicles 104 with thelocation 204 affected by thetransit event 110 than localized broadcast message channels, which may be limited by such factors as range restrictions and interference. For example, the techniques presented herein may utilize an internet connection of a mobile device for the exchange ofnotifications 210, and internet connectivity may be both more well-developed and more ubiquitous than specialized equipment and support for a localized broadcast message channel such as traffic messaging systems (TMS). - As a second such example, the techniques provided herein may enable greater selectivity of the transmission of
notifications 210, i.e., limiting the transmission ofnotifications 210 to thevehicles 104 that are affected by thetransit event 110. Such selectivity may raise the signal-to-noise ratio of the notification system; may conserve the computational and messaging resources utilized in such delivery; and/or may enable faster delivery of such notifications 210 (e.g., by avoiding circumstances where the transmission of afirst notification 210 that is relevant to thevehicles 104 in aparticular location 204 is delayed by the transmission of asecond notification 210 that does not apply to thevehicles 104 or the location 204). - As a third such example, the techniques provided herein may scale to support a large number of
vehicles 104 and/ortransit events 106, without incurring scalability penalties such as latency. Atransit service 202 that receives anotification 208 and may utilize readily-availablevehicle area groups 206 to determine theother vehicles 104 that are to receive thebroadcast notification 210 may achieve such delivery faster than atransit service 202 that, ad-hoc, identifies thevehicles 104 to receive thebroadcast notification 210 among a potentially large set of millions ofvehicles 104. Many such technical effects may arise from the broadcasting ofnotifications 210 oftransit events 110 in accordance with the techniques presented herein. - D. Example Embodiments
-
FIG. 3 presents a first example embodiment of the techniques presented herein, illustrated as anexample method 300 of broadcastinglocalized transit events 110 detected during transit of avehicle 104. Theexample method 300 may be implemented on a device having a processor, and that is in communication with atransit service 202 having information about thelocations 206 of thearea 108. Theexample method 300 may be implemented, e.g., as a set of instructions stored in a memory component of the device (e.g., a memory circuit, a platter of a hard disk drive, a solid-state memory component, or a magnetic or optical disc) that, when executed by the processor of the device, cause the device to perform the techniques presented herein. - The
example method 300 begins at 302 and involves executing 304 the instructions on the processor. Specifically, the instructions cause the device to detect 306 alocation 204 of thevehicle 104. The instructions also cause the device to transmit thelocation 204 to thetransit service 202 to add thevehicle 104 to avehicle area group 206 for thelocation 204. The instructions also cause the device to, upon detecting atransit event 110 in thelocation 204 of thevehicle 104, transmit 310 thetransit event 110 to thetransit service 202 for broadcasting toother vehicles 104 of thevehicle area group 206. The instructions also cause the device to, upon receiving from the transit service 202 anotification 210 of atransit event 110 for thevehicle area group 206, utilize 312 thenotification 210 in the transit of thevehicle 104. In this manner, theexample method 300 enables thevehicle 104 to participate in the exchange ofnotifications 210 about thetransit events 110 arising within thearea 108 through interaction with atravel service 202 provided in accordance with the techniques presented herein, and so ends at 314. -
FIG. 4 presents an illustration of anexample scenario 400 featuring a second example embodiment of the techniques presented herein, illustrated as anexample server 402 comprising asystem 410 that provides atransit service 202 to a set ofvehicles 104. Theexample system 410 may be implemented, e.g., on aserver 402 having aprocessor 404, amemory 408, and avehicle communicator 406 that communicates with thevehicles 104. A portion of theserver 402 and/ortraffic service 202 may be located within thevehicle 104 of theuser 102, and/or may be located at a remote location. Respective components of theexample system 410 may be implemented, e.g., as a set of instructions stored in amemory 408 of theserver 402 and executable on theprocessor 404 of theserver 402, such that the interoperation of the components causes theserver 402 to operate according to the techniques presented herein. - The
example system 410 comprises a vehiclearea group manager 412, which, upon receiving alocation 204 of avehicle 104, adds thevehicle 104 to avehicle area group 210 for thelocation 204. Thesystem 410 also comprises atransit event broadcaster 414, which, upon receiving, from avehicle 104, anotification 208 of atransit event 110 for thelocation 204, identifies at least oneother vehicle 104 of thevehicle area group 206, and broadcasts to the at least oneother vehicle 104 of the vehicle area group 206 anotification 210 of thetransit event 110. In this manner, theexample system 410 provides atravel service 202 that facilitates the exchange ofnotifications 210 about thetransit events 110 of thelocation 204 in accordance with the techniques presented herein. -
FIG. 5 presents an illustration of anexample scenario 500 featuring a third example embodiment of the techniques presented herein, illustrated as anexample vehicle device 502 featuring anexample system 514 that enables avehicle 104 to exchangenotifications 210 withother vehicles 104 abouttransit events 110 arising in thelocation 204 of thevehicles 104. Theexample system 514 may be implemented, e.g., on avehicle device 502 having aprocessor 504; amemory 512; alocation detector 506 that detects alocation 204 of the vehicle 104 (e.g., a global positioning system (GPS) coordinate); atransit service communicator 508 that communicates with a transit service 202 (e.g., a wireless network adapter that is connected to thetransit service 202 via an internet connection); and atransit event detector 510 that detects atransit event 110 in thelocation 204 of thevehicle 104. Respective components of theexample system 514 may be implemented, e.g., as a set of instructions stored in thememory 512 of thevehicle device 502 and executable on theprocessor 504 of thevehicle device 502, such that the interoperation of the components causes thevehicle device 502 to operate according to the techniques presented herein. - The
example system 514 comprises a transit service interface, which transmits thelocation 204 of thevehicle 104, via thetransit service communicator 508, to thetransit service 202 in order to add thevehicle 104 to avehicle area group 206 for thelocation 204, and also transmits to thetransit servicer 202, via thetransit service communicator 508, anotification 208 of thetransit event 110 for broadcasting toother vehicles 104 of thevehicle area group 206. Theexample system 514 also comprises alocal event notifier 518, which, upon receiving from the transit service 202 anotification 210 of atransit event 110 for thevehicle area group 206, utilizes thenotification 210 in the transit of the vehicle 104 (e.g., by presenting thenotification 210 to theuser 102; by adjusting an autonomous control system of thevehicle 104; and/or by adjusting a route selected by theuser 102 to reach a destination). In this manner, theexample system 514 may enable thevehicle device 502 to exchangenotifications 210 about thetransit events 110 arising within thelocation 204 in accordance with the techniques presented herein. - Still another embodiment involves a computer-readable medium comprising processor-executable instructions configured to apply the techniques presented herein. Such computer-readable media may include, e.g., computer-readable storage media involving a tangible device, such as a memory semiconductor (e.g., a semiconductor utilizing static random access memory (SRAM), dynamic random access memory (DRAM), and/or synchronous dynamic random access memory (SDRAM) technologies), a platter of a hard disk drive, a flash memory device, or a magnetic or optical disc (such as a CD-R, DVD-R, or floppy disc), encoding a set of computer-readable instructions that, when executed by a processor of a device, cause the device to implement the techniques presented herein. Such computer-readable media may also include (as a class of technologies that are distinct from computer-readable storage media) various types of communications media, such as a signal that may be propagated through various physical phenomena (e.g., an electromagnetic signal, a sound wave signal, or an optical signal) and in various wired scenarios (e.g., via an Ethernet or fiber optic cable) and/or wireless scenarios (e.g., a wireless local area network (WLAN) such as WiFi, a personal area network (PAN) such as Bluetooth, or a cellular or radio network), and which encodes a set of computer-readable instructions that, when executed by a processor of a device, cause the device to implement the techniques presented herein.
- An example computer-readable medium that may be devised in these ways is illustrated in
FIG. 6 , wherein theimplementation 600 comprises a computer-readable medium 602 (e.g., a CD-R, DVD-R, or a platter of a hard disk drive), on which is encoded computer-readable data 604. This computer-readable data 604 in turn comprises a set ofcomputer instructions 606 configured to operate according to the principles set forth herein. As a first such example, thecomputer instructions 606 may cause thedevice 610 to utilize a method of exchangingnotifications 210 oftransit events 110 within alocation 204 withother vehicles 104 in thelocation 206, such as theexample method 300 ofFIG. 3 . As a second such example, thecomputer instructions 606 may provide a system for providing atransit service 202 to a set ofvehicles 104 operating in alocation 204, such as theexample system 410 in theexample scenario 400 ofFIG. 4 . As a third such example, thecomputer instructions 606 may provide a system for exchangingnotifications 210 oftransit events 110 within alocation 204 withother vehicles 104 in thelocation 206, such as theexample system 514 in theexample scenario 500 ofFIG. 5 . Many such computer-readable media may be devised by those of ordinary skill in the art that are configured to operate in accordance with the techniques presented herein. - E. Variable Aspects
- The techniques discussed herein may be devised with variations in many aspects, and some variations may present additional advantages and/or reduce disadvantages with respect to other variations of these and other techniques. Moreover, some variations may be implemented in combination, and some combinations may feature additional advantages and/or reduced disadvantages through synergistic cooperation. The variations may be incorporated in various embodiments (e.g., the
example method 300 ofFIG. 3 ; theexample system 410 ofFIG. 4 ; theexample system 512 ofFIG. 5 ; and the example computer-readable storage device 602 ofFIG. 6 ) to confer individual and/or synergistic advantages upon such embodiments. - E1. Scenarios
- A first aspect that may vary among embodiments of these techniques relates to the scenarios wherein such techniques may be utilized.
- As a first variation of this first aspect, the techniques presented herein may be used with many types of
vehicles 104, including automobiles, motorcycles, trucks, trains, buses, watercraft, aircraft, drones, and spacecraft. Such vehicles may be controlled by one or more humans, may be autonomous, or may involve a combination thereof, such as an autonomous automobile that can also be controlled by a human. - As a second variation of this first aspect, the techniques presented herein may be utilized to provide advise
users 102 of events occurring in many types ofareas 108 and/orlocations 202, such as a roadway, highway, sidewalk, dirt or grass path, waterway, and airspace.Such areas 108 may also be defined statically, e.g., as the boundary of a municipality or a set of global positioning system (GPS) coordinates that define the boundaries of anarea 108, may be defined dynamically, e.g., as anarea 108 where an event such as a convention is occurring, or anarea 108 where traffic congestion has been detected. - As a third variation of this first aspect, the techniques presented herein may be utilized to exchange
notifications 210 about many types oftransit events 110 occurring in anarea 108, such as vehicular accidents; the formation of traffic congestion, such as due to high vehicle volume or construction; an obstruction, such as debris or wildlife; a hazardous condition in thelocation 204, such as a fire; and weather events, such as the formation of ice or flooding. Many such variations may arise within the set of scenarios in which the techniques presented herein may be utilized. - E2. Transit Event Detection
- A second aspect that may vary among embodiments of these techniques involves the detection of the occurrence of the
transit event 110, including information about thetransit event 110 that may advise theother vehicles 104 as to how to respond to thetransit event 110. - As a first variation of this second aspect, a vehicle device may receive a report of a
transit event 110 directly from theuser 102 within thevehicle 104. For example, theuser 102 may initiate a voice report of an observedtransit event 110, and the vehicle device may transmit the voice report of theuser 102 to thetransit service 202. - As a second variation of this second aspect, a vehicle device may evaluate telemetry of the
vehicle 104 to detect atransit event 110. For example, telemetry indicating that theuser 102 has engaged windshield wipers or fog lamps may indicate the presence of transit-affecting weather conditions in thelocation 204, and telemetry indicating an engagement of an anti-lock braking system in a particular location 204 (coupled with weather data indicating freezing weather) may indicate atransit event 110 involving the formation of ice on a road surface of in thelocation 204 -
FIG. 7 presents an illustration of anexample scenario 700 featuring a third variation of this second aspect, involving a proximity sensor that generates proximity data indicating a proximity of the vehicle to a second vehicle, and a proximity data evaluator that evaluates the proximity data to identify thetransit event 110. In thisexample scenario 700, a lane of a road occupied by avehicle 104 of theuser 102 is detected according to aproximity sensor 702 of thevehicle 104.Such proximity sensors 702 may utilize a variety of techniques for such detection, including visual evaluation of camera data; ranging data gathered by sonar, radar, and/or lidar detection; and/or electronic communication withother vehicles 104 in thelocation 204. In thisexample scenario 700, thevehicle 104 is equipped with aproximity sensor 702 that detects a proximity of thevehicle 104 with respect toother vehicles 104 operating in thelocation 204, such as adistance 704 between thevehicle 104 and anothervehicle 104 that is ahead of and/or behind thevehicle 104 of theuser 102; the relative speeds of thevehicles 104 ahead of and/or behind theuser 102; and/or the rates of acceleration, braking, turning, and/or swerving by theuser 102 and thedrivers 106 of theother vehicles 104. Theproximity sensor 702 may also detect information aboutvehicles 104 in other lanes of the road, such as the relative or absolute speeds ofvehicles 104 in adjacent lanes and/or passing in the other direction of transit, and/or whether or notsuch vehicles 104 are passing 706 and/or are being passed by thevehicle 104. Moreover, such proximity data may be evaluated to detect atransit event 110. As a first such example, theproximity sensor 702 may detect one ormore vehicles 104 that are stationary in an adjacent lane, in the median of the road, and/or off to the side of the road, may indicate the occurrence of a vehicular accident and position thereof in thelocation 204. As a second such example, theproximity sensor 702 may detect sudden changes in the proximity of thevehicles 104 indicating atransit event 110, such as a rapid deceleration of avehicle 104 behind thevehicle 104 of theuser 102 that indicates a collision. Thevehicle device 708 may utilize theproximity sensor 704 to detectsuch transit events 110, and may send anotification 208 of thetransit events 110 to thetransit service 202. -
FIG. 8 presents an illustration of example scenarios featuring a fourth set of variations of this second aspect, wherein atransit event 110 is detected bymachine vision techniques 808. As afirst example scenario 802, avehicle device 708 on board thevehicle 104 may include and/or be in communication with a forward-mountedcamera 802 that captures a forward-facing image 804 (e.g., through awindshield 806 of the vehicle 104). Amachine vision technique 808, such as an object recognition algorithm, may be applied to theimage 804, such as an object recognition technique that recognizesvehicles 104; extrapolates their positions within thelocation 204, and/or details such as their directions, speeds, and acceleration; and, by modeling their positions, identifies that a collision has occurred. A secondmachine vision technique 808 may be applied that utilizes a line detection algorithm to detect visible lines of the road that indicate lanes, including a current lane of thevehicle 104 of theuser 102. The position of thevehicle 104 on the road may therefore be extrapolated by themachine vision technique 808, and this information may be utilized to provide additional information about the transit event 110 (e.g., which lane(s) thetransit event 110 affects) and/or to adjust the navigation of thevehicle 104 and/or advise the user 102 (e.g., determining whether the current lane of thevehicle 104 avoids or is obstructed by the transit event 110). Alternatively or additionally, other machine vision techniques may be applied to theimage 804 to about thetransit event 110, such as object recognition to detect and optionally count a number ofvisible vehicles 104 ahead of thevehicle 104 of theuser 102 in the respective lanes as a measurement of traffic congestion, and/or visual sizing machine vision techniques that estimate a distance ofvehicles 104 ahead of thevehicle 104 of theuser 102. As asecond example scenario 810, a downward-facingcamera 802 may capture a downward-facingimage 804 of thelocation 204; an object recognition algorithm may be applied to detect objects that are visible on the surface of the road and that may indicate atransit event 110, such as ice, water, debris, or potholes; and a line detectionmachine vision technique 808 may be utilized to detect the visible lines indicating the lanes of the road, and/or the current lane that is currently occupied by thevehicle 104 of theuser 102. Many such techniques may be utilized to detect and describetransit events 110 occurring within thelocation 204 of thevehicle 104 for reporting to thetransit service 202 in accordance with the techniques presented herein. - E3. Exchange Protocol
- A third aspect that may vary among embodiments of the techniques presented herein involves the manner of exchanging
notifications 210 oftransit events 110 among thevehicles 104 and thetransit service 202. - As a first variation of this third aspect, vehicle devices and
travel service 202 may communicate through a wide range of communication channels, such as electromagnetic wave transmissions at various frequencies. Such communication channels may also be utilized to exchangenotifications 210 encoded in various ways, such as a human-receivable voice or tone; a human-readable message, such as text, images, and/or video; encoded data that describes thetransit event 110, such as an extensible markup language (XML) providing fields that identify properties of thetransit event 110 such as its precise location, type, and severity; and/or encoded data that provides instructions for autonomous control of a vehicle navigation system, such as instructions to engage a braking system to slow or halt thevehicle 104, and/or instructions to re-route the transit of thevehicle 104 through an alternative area. Many such communications protocols may be utilized to deliversuch notifications 210 over the selected messaging channels, such as messages exchanged using a variant of the hypertext transport protocol (HTTP), including a websockets interface. As one such example, avehicle communicator 406 of aserver 402 providing thetravel service 202 may comprise an internet connection that communicates with vehicle devices through the internet using a websocket protocol. A vehiclearea group manager 412 may, in addition to adding avehicle 104 to avehicle area group 206, allocate a websocket to communicate with thevehicle 104 through the internet using the websocket protocol; and thetransit event broadcaster 414 may broadcast the notification of thetransit event 110 to therespective vehicles 104 through the respective websockets. Similarly, thetransit service communicator 508 of avehicle 104 may further comprise an internet connection through which thetransit service communicator 508 communicates with thetransit service 202 using a websocket protocol, and thelocal event notifier 518 may receive thenotification 210 of thetransit event 110 from thetransit service 202 through a websocket of the websocket protocol that has been allocated to communicate with thetransit service 202. The selection of a protocol such as websockets may enable further advantages, such as a reduced reliance on ping or keepalive messages to maintain the communication channel; as a result, the communication resources (e.g., radiofrequency bandwidth) may be conserved for the actual exchange ofnotifications 210 oftransit events 110, which may also reduce the latency in the delivery ofsuch notifications 210, and the scalability to support broadcasting to a large number ofvehicles 104 in aparticular location 204 with reduced interference. Websockets may also be advantageous due to the greater incidence of interruption of connectivity ofvehicles 104 in transit, since ephemeral lapses in connectivity may not necessitate the exchange of network communication, but may be tolerated as part of thetransit service 202. - As a second variation of this third aspect, many mechanisms may be utilized to associated
vehicles 104 with vehicle area groups 206. As one such example, atransit service 202 may, upon receiving from the vehicle afirst location 204, determine whether avehicle area group 206 exists for thefirst location 204, and upon determining that avehicle area group 206 does not exist for thefirst location 204, create avehicle area group 206 for thefirst location 204. Thetransit service 202 may also, upon receiving from the vehicle 104 asecond location 204 of the vehicle 204 (e.g., an updated global positioning service (GPS) coordinate), determine whether thesecond location 204 is also associated with thevehicle area group 206; and upon determining that thesecond location 204 is not associated with thevehicle area group 206, remove thevehicle 104 from thevehicle area group 206 for the first location 204 (e.g., transferring the association of thevehicle 104 from the firstvehicle area group 206 for thefirst location 204 to a secondvehicle area group 206 for the second location 204). -
FIG. 9 presents an illustration of anexample scenario 900 featuring a third set of variations of this third aspect involving the broadcasting ofvarious notifications 208 oftransit events 110 for alocation 204. In thisexample scenario 900, in addition to thetransit service 202 receivingnotifications 208 fromvehicles 104 that are enrolled in thetransit service 202 and broadcastingsuch notifications 208 to theother vehicles 104 of thevehicle area group 206 that are also enrolled in thetransit service 202, thetransit service 202 may be utilized to retransmitnotifications 208 generated by other services, and vice versa. - As a first such example, a
vehicle device 706 may further comprise a local transit event rebroadcaster that locally rebroadcasts thenotification 206 of thetransit event 110 over a localized broadcast messaging channel. For example, after detecting atransit event 210 and transmitting thenotification 208, and/or after receiving anotification 210 from thetransit service 202, a vehicle device 2706 may utilize atransmitter 116 broadcast thenotification 208 using a local broadcast messaging channel, such as a local, low-power radiofrequency (RF) broadcast, or a directed vehicle-to-vehicle communication channel. Areceiver 120 within asecond vehicle 104 that is not enrolled in thetransit service 202, and/or that is enrolled but that is not in communication with thetransit service 202 due to a temporary communication interruption, may therefore receive the local broadcast. - As a second such example, a localized broadcast channel monitor may be utilized to monitor a localized broadcast messaging channel, such as broadcasts by a regional broadcast tower 112 (e.g., a traffic message channel (TMS) broadcaster), and may retransmit
notifications 210 oftransit events 110 received through such a localized broadcast messaging channel to thetransit service 202 for rebroadcasting to theother vehicles 104 of thevehicle area group 206 for thelocation 204 involved in thetransit event 110. As another such variation, the transit service may remotely monitor sources of information abouttransit events 110, such as traffic message channel (TMS) information provided over the internet, and may broadcastnotifications 210 oftransit events 110 according to thevehicle area groups 206 for thelocations 204 involved in thetransit events 110. Such broadcasting may enable delivery of the localized broadcast message toother vehicles 104 that are not monitoring the localized broadcast messaging channel, but that are in communication with thetransit service 202. Conversely, thetransit service 202 and/or thevehicle device 706 may also provide information to other services for transmission via localized broadcast messaging channels. For example, upon receiving anotification 208 from avehicle 104 in alocation 204 of atransit event 110, thetransit service 202 may, in addition to broadcasting anotification 210 to thevehicles 104 of thevehicle area group 206, transmit thenotification 210 to theregional broadcast tower 112 for regional rebroadcast. Alternatively, thevehicle device 706 may transmit thenotification 208 to the to theregional broadcast tower 112 for regional rebroadcast. Such rebroadcasting techniques may coordinate the exchange ofnotifications 210 among thevehicles 104 enrolled in thetransit service 202 with the exchange ofnotifications 210 amongother vehicles 104 that are not enrolled in thetransit service 202, and/or that have lost communication with thetransit service 202. -
FIG. 10 presents an illustration of anexample scenario 1000 featuring further variations of this third aspect involving the broadcasting ofvarious notifications 208 oftransit events 110 forvarious locations 204. In thisexample scenario 1000, in addition to thetransit service 202 receivingnotifications 208 fromvehicles 104 that are enrolled in thetransit service 202 and broadcastingsuch notifications 208 to theother vehicles 104 of thevehicle area group 206 in the samevehicle area group 206 for thesame location 204, thetransit service 202 may also determine other recipients of the information to which thenotification 210 of thetransit event 110 may apply. - As a fourth variation of this third aspect presented in
FIG. 10 , thetransit service 202 receives anotification 208 of a multi-vehicle accident in aparticular location 204, and, in addition to identifying thevehicles 104 within thevehicle area group 206 for thethird location 204, may evaluate asecond location 204 that may also be affected by thetransit event 110, such as a distant stretch of the road that approaches the site of thetransit event 110; an entrance ramp of a nearby road that leads to thetransit event 110; or a second road that passes over or under the site of thetransit event 110. Thetransit service 202 may determine whether thetransit event 110 applies to thevehicles 104 of thesecond location 204, and may broadcast thenotification 210 to thevehicles 104 in thevehicle area group 206 of thesecond location 204. For example, a weather-related event that is detected in afirst location 204 may be projected as following a weather pattern (such as a wind direction) that is likely to affect asecond location 204, and thetransit service 202 may broadcast thenotification 210 to thevehicles 104 in thevehicle area group 206 for thesecond location 204. - As a fifth variation of this third aspect, the
notification 210 may be updated to reflect a recommendation to thevehicles 104, including theuser 104 and theother drivers 106, as to how to respond to thetransit event 110. For example, thesecond location 204 features adetour option 1002 for avoiding the location of thetransit event 110, such as an exit ramp, an alternate route, or a second lane of a road that is not affected by thetransit event 110 that impacts a first lane of the road. The transit service 220 may therefore add, to thenotification 210 broadcast to thevehicles 104 of thevehicle area group 206, arecommendation 1004 to take thedetour option 1002 to avoid thelocation 204 of thetransit event 110. - As a sixth variation of this third aspect presented in
FIG. 10 , thetransit service 202 may be configured to notify first responders as to the occurrence of atransit event 110, where such first responders provide a first response service relating to thetransit event 110 for thelocation 204. For example, thetransit service 202 may evaluate the information about thetransit event 110 and may determine whether police, fire control personnel, medical personnel, tow trucks, or mechanics are to be directed to thelocation 204 of thetransit event 110. Thetransit service 202 may therefore generate anotification 1006 to thefirst responders 1008, and may transmit thenotification 1006 of thetransit event 110 to thefirst responders 1008. - As a seventh variation of this third aspect, the
transit service 202 may comprise a transit event verifier that endeavors to verify thetransit events 110 reported byrespective vehicles 104. For example, atransit event 110 involving a sudden braking incident by avehicle 104 may indicate atransit event 110 such as an accident or ice, for which anotification 210 of thetransit event 110 is to broadcast. However, the sudden braking may also indicate a transient event, such as a brief encounter with wildlife, or a vehicle or driver error, such as accidentally activating the brakes or misperceiving the presence of a vehicle in a nearby lane. Before broadcasting thenotification 210, thetransit service 202 may endeavor to verify thetransit event 110 by identifying asecond vehicle 104 of thevehicle area group 206 that is capable of verifying thetransit event 110, and transmitting to the second vehicle 104 a request to verify the transit event 110 (e.g., by asking thedriver 106 of thesecond vehicle 104 to confirm or refute thetransit event 110, and/or by utilizing sensors of the second vehicle 104). The broadcasting of thenotification 210 may be contingent upon first receiving a verification of thetransit event 110 from thesecond vehicle 104. - As an eighth variation of this third aspect, before broadcasting a
notification 210 toother vehicles 104 of avehicle area group 206, thetransit service 202 may utilize various techniques to anonymize thevehicle 104 that transmitted thenotification 208 of the thetransit event 110. For example, thetransit service 202 may extrapolate the GPS coordinate transmitted by thevehicle 104 to the GPS coordinate of thetransit event 110, and may include the latter GPS coordinate but not the former GPS coordinate that identifies whichvehicle 104 transmitted thetransit event 110. As another such example, where thenotification 210 includes an image or voice recording of thetransit event 110 captured by thevehicle 104 and/or theuser 102, such as the user's name or a vehicle identifier of the vehicle 104 (e.g., the license plate), thetransit service 202 may remove identifying features of such media before broadcast to theother vehicles 104 of thevehicle area group 206. Many such techniques may be included in the exchange ofnotifications 210 oftransit events 110 in accordance with the techniques presented herein. - E4. Utilizing Transit Event Notification
- A fifth aspect that may vary among embodiments of the techniques presented herein involves the manner of utilizing a transit event during the transit of the
vehicle 104, such as advising auser 102 of the occurrence and details of atransit event 110. - As a first variation of this fourth aspect, information about the
transit event 110 may be described to theuser 102 in a variety of ways. As a first such example, thetransit event 110 may be described in absolute terms (e.g., “warning: accident at northbound 14 kilometer mark”) or in relative terms (e.g., “warning: accident one kilometer ahead”), and may include a recommendation to theuse 102 to adjust the control of the vehicle 104 (e.g., “reduce speed by 10 kph” or “engage fog lamps”). As a second such example, thedevice 202 may or may not explain the basis of a recommendation responsive to thetransit event 110, e.g., why theuser 102 is advised to choose an alternate route or lane of a road. Moreover, if thetransit event 110 does not result in a recommendation to theuser 102 to do anything else (e.g., if the safest path past a vehicular accident is the lane that thevehicle 104 currently occupies), avehicle device 708 may either present the recommendation (e.g., “recommendation: maintain current lane”), or may defer such recommendation until detecting that theuser 102 is considering transitioning to a different lane (e.g., upon detecting the user's activation of a turn signal). As still another example, the transit of thevehicle 104 may be controlled by a vehicle control system according to a driving behavior profile, and thetransit event 110 may prompt thevehicle 104 to the driving behavior profile of the vehicle control system in response to the transit event 110 (e.g., reducing a cruise-control speed of thevehicle 104, engaging a braking system, and/or adjusting a route for the transit of thevehicle 104 to choose an alternative route that avoids the transit event 110). -
FIG. 11 presents an illustration of a set ofexemplary scenarios 1100 whereby avehicle device 708 may notify theuser 102 about atransit event 110. As asecond variation 1102 of this fifth aspect, a visual and/or audial indicator may be presented to theuser 102 by thevehicle device 708 and/orvehicle 104, such as a light on the dashboard of thevehicle 104 or an audio orvoice cue 1104 prompting the user to select aparticular lane 1112 to avoid thetransit event 110. As athird variation 1106 of this fifth aspect, avisual indicator 1110 may be presented on awindow 1108 of thevehicle 104, and, optionally, may be presented at a selectedlocation 1114 on thewindow 1108 that correlates thevisual indicator 1110 with thelocation 1112 of thetransit event 110 through thewindow 1108 from the perspective of the user 102 (e.g., presenting a visual arrow and/or highlighting the location of thetransit event 110 when viewed through thewindow 1108 by the user 102). As afourth variation 1114 of this fifth aspect, theuser 102 may wear one or more wearable devices while operating thevehicle 104, such as a pair ofeyeglasses 1116 or awristwatch 1118. The presentation of thenotification 210 of thetransit event 110 may be achieved through such wearable devices, e.g., by presenting avisual indicator 1120 within the viewable region of theeyeglasses 1116 worn by theuser 102, and/or issuing avibration alert 1122 through thewristwatch 1118 of theuser 102 to indicate the location of the transit event 110 (e.g., flashing a leftwardvisual indicator 1120 or avibration alert 1122 on the user's left wrist to draw the user's attention to the left lane where atransit event 110 has occurred). Many such techniques may be utilized to present to theuser 102 thenotification 210 of thetransit event 110 in accordance with the techniques presented herein. - F. Computing Environment
-
FIG. 12 and the following discussion provide a brief, general description of a suitable computing environment to implement embodiments of one or more of the provisions set forth herein. The operating environment ofFIG. 12 is only one example of a suitable operating environment and is not intended to suggest any limitation as to the scope of use or functionality of the operating environment. Example computing devices include, but are not limited to, personal computers, server computers, hand-held or laptop devices, mobile devices (such as mobile phones, Personal Digital Assistants (PDAs), media players, and the like), multiprocessor systems, consumer electronics, mini computers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. - Although not required, embodiments are described in the general context of “computer readable instructions” being executed by one or more computing devices. Computer readable instructions may be distributed via computer readable media (discussed below). Computer readable instructions may be implemented as program modules, such as functions, objects, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types. Typically, the functionality of the computer readable instructions may be combined or distributed as desired in various environments.
-
FIG. 12 illustrates an example of asystem 1200 comprising acomputing device 1202 configured to implement one or more embodiments provided herein. In one configuration,computing device 1202 includes at least oneprocessing unit 1206 andmemory 1208. Depending on the exact configuration and type of computing device,memory 1208 may be volatile (such as RAM, for example), non-volatile (such as ROM, flash memory, etc., for example) or some combination of the two. This configuration is illustrated inFIG. 12 by dashedline 1204. - In other embodiments,
device 1202 may include additional features and/or functionality. For example,device 1202 may also include additional storage (e.g., removable and/or non-removable) including, but not limited to, magnetic storage, optical storage, and the like. Such additional storage is illustrated inFIG. 12 bystorage 1210. In one embodiment, computer readable instructions to implement one or more embodiments provided herein may be instorage 1210.Storage 1210 may also store other computer readable instructions to implement an operating system, an application program, and the like. Computer readable instructions may be loaded inmemory 1208 for execution byprocessing unit 1206, for example. - The term “computer readable media” as used herein includes computer storage media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions or other data.
Memory 1208 andstorage 1210 are examples of computer storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed bydevice 1202. Any such computer storage media may be part ofdevice 1202. -
Device 1202 may also include communication connection(s) 1216 that allowsdevice 1202 to communicate with other devices. Communication connection(s) 1216 may include, but is not limited to, a modem, a Network Interface Card (NIC), an integrated network interface, a radio frequency transmitter/receiver, an infrared port, a USB connection, or other interfaces for connectingcomputing device 1202 to other computing devices. Communication connection(s) 1216 may include a wired connection or a wireless connection. Communication connection(s) 1216 may transmit and/or receive communication media. - The term “computer readable media” may include communication media. Communication media typically embodies computer readable instructions or other data in a “modulated data signal” such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” may include a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal.
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Device 1202 may include input device(s) 1214 such as keyboard, mouse, pen, voice input device, touch input device, infrared cameras, video input devices, and/or any other input device. Output device(s) 1212 such as one or more displays, speakers, printers, and/or any other output device may also be included indevice 1202. Input device(s) 1214 and output device(s) 1212 may be connected todevice 1202 via a wired connection, wireless connection, or any combination thereof. In one embodiment, an input device or an output device from another computing device may be used as input device(s) 1214 or output device(s) 1212 forcomputing device 1202. - Components of
computing device 1202 may be connected by various interconnects, such as a bus. Such interconnects may include a Peripheral Component Interconnect (PCI), such as PCI Express, a Universal Serial Bus (USB), firewire (IEEE 1394), an optical bus structure, and the like. In another embodiment, components ofcomputing device 1202 may be interconnected by a network. For example,memory 1208 may be comprised of multiple physical memory units located in different physical locations interconnected by a network. - Those skilled in the art will realize that storage devices utilized to store computer readable instructions may be distributed across a network. For example, a
computing device 1220 accessible vianetwork 1218 may store computer readable instructions to implement one or more embodiments provided herein.Computing device 1202 may accesscomputing device 1220 and download a part or all of the computer readable instructions for execution. Alternatively,computing device 1202 may download pieces of the computer readable instructions, as needed, or some instructions may be executed atcomputing device 1202 and some atcomputing device 1220. - G. Usage of Terms
- Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
- As used in this application, the terms “component,” “module,” “system”, “interface”, and the like are generally intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a controller and the controller can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers.
- Furthermore, the claimed subject matter may be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter. The term “article of manufacture” as used herein is intended to encompass a computer program accessible from any computer-readable device, carrier, or media. Of course, those skilled in the art will recognize many modifications may be made to this configuration without departing from the scope or spirit of the claimed subject matter.
- Various operations of embodiments are provided herein. In one embodiment, one or more of the operations described may constitute computer readable instructions stored on one or more computer readable media, which if executed by a computing device, will cause the computing device to perform the operations described. The order in which some or all of the operations are described should not be construed as to imply that these operations are necessarily order dependent. Alternative ordering will be appreciated by one skilled in the art having the benefit of this description. Further, it will be understood that not all operations are necessarily present in each embodiment provided herein.
- Moreover, the word “example” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “example” is not necessarily to be construed as advantageous over other aspects or designs. Rather, use of the word example is intended to present concepts in a concrete fashion. As used in this application, the term “or ” is intended to mean an inclusive “or ” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X employs A or B” is intended to mean any of the natural inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, then “X employs A or B” is satisfied under any of the foregoing instances. In addition, the articles “a” and “an ” as used in this application and the appended claims may generally be construed to mean one or more unless specified otherwise or clear from context to be directed to a singular form.
- Also, although the disclosure has been shown and described with respect to one or more implementations, equivalent alterations and modifications will occur to others skilled in the art based upon a reading and understanding of this specification and the annexed drawings. The disclosure includes all such modifications and alterations and is limited only by the scope of the following claims. In particular regard to the various functions performed by the above described components (e.g., elements, resources, etc.), the terms used to describe such components are intended to correspond, unless otherwise indicated, to any component which performs the specified function of the described component (e.g., that is functionally equivalent), even though not structurally equivalent to the disclosed structure which performs the function in the herein illustrated example implementations of the disclosure. In addition, while a particular feature of the disclosure may have been disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular application. Furthermore, to the extent that the terms “includes”, “having”, “has”, “with”, or variants thereof are used in either the detailed description or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.”
Claims (20)
1. A method of broadcasting localized transit events detected during transit of a vehicle, the method involving a device having a processor and in communication with a transit service and comprising:
executing, on the processor, instructions that cause the device to:
detect a location of the vehicle;
transmit the location to the transit service to add the vehicle to a vehicle area group for the location;
upon detecting a transit event in the location of the vehicle, transmit the transit event to the transit service for broadcasting to other vehicles of the vehicle area group; and
upon receiving from the transit service a notification of a transit event for the vehicle area group, utilize the notification in the transit of the vehicle.
2. The method of claim 1 , wherein utilizing the notification in the transit of the vehicle further comprises: presenting the notification to a user within the vehicle.
3. The method of claim 2 , wherein:
the vehicle further comprises a window; and
presenting the notification to the user further comprises: displaying the notification on the window of the vehicle.
4. The method of claim 1 , wherein:
the transit event relates to a route of the transit of the vehicle; and
utilizing the notification in the transit of the vehicle further comprises: adjusting the route of the vehicle in response to the transit event.
5. The method of claim 1 , wherein:
the transit of the vehicle is controlled by a vehicle control system according to a driving behavior profile; and
utilizing the notification in the transit of the vehicle further comprises: adjusting the driving behavior profile of the vehicle control system in response to the transit event.
6. A server that provides a transit service to vehicles, the server comprising:
a processor;
a vehicle communicator that communicates with the vehicles; and
a memory storing instructions that, when executed by the processor, provide a system comprising:
a vehicle area group manager that, upon receiving a location of a vehicle, adds the vehicle to a vehicle area group for the location; and
a transit event broadcaster that, upon receiving, from a vehicle, a transit event for the location:
identifies at least one other vehicle of the vehicle area group; and
broadcasts to the at least one other vehicle of the vehicle area group a notification of the transit event.
7. The server of claim 6 , wherein the system further comprises: a vehicle anonymizer that:
identifies, in the notification of the transit event, a vehicle identifier that identifies the vehicle that transmitted the transit event; and
removes the vehicle identifier from the notification of the transit event.
8. The server of claim 6 , wherein the server adds the vehicle to the vehicle area group by:
upon receiving from the vehicle a first location:
determining whether a vehicle area group exists for the first location;
upon determining that a vehicle area group does not exist for the first location, creating a vehicle area group for the first location; and
upon receiving from the vehicle a second location:
determining whether the second location is associated with the vehicle area group; and
upon determining that the second location is not associated with the vehicle area group, removing the vehicle from the vehicle area group for the first location.
9. The server of claim 6 , wherein the server further comprises: a vehicle area group evaluator that, upon receiving a notification of a transit event for the location:
identifies a second location that is affected by the transit event;
identifies at least one vehicle of a second vehicle area group for the second location; and
broadcasts the notification of the transit event to the at least one vehicle of the second vehicle area group.
10. The server of claim 9 , wherein:
the second location features a detour option for avoiding the location of the transit event; and
broadcasting the notification of the transit event to the second vehicle area group further comprises: adding to the notification a recommendation to take the detour option to avoid the location of the transit event.
11. The server of claim 9 , wherein the system further comprises: a first responder notifier that:
identifies a first responder that provides a first response service relating to the transit event for the location; and
transmits the notification of the transit event to the first responder.
12. The server of claim 6 , wherein the system further comprises:
a transit event verifier that, upon receiving the notification of the transit event:
identifies a second vehicle of the vehicle area group that is capable of verifying the transit event, and
transmits to the second vehicle a request to verify the transit event; and
broadcasting the notification to the vehicle area group further comprises: broadcasting the notification of the transit event to the at least one other vehicle of the vehicle area group only after receiving a verification of the transit event from the second vehicle.
13. The server of claim 6 , wherein:
the vehicle communicator comprises an internet connection that communicates with a device of the vehicle through the internet using a websocket protocol;
the vehicle area group manager adds the vehicle to the vehicle area group by allocating a websocket to communicate with the vehicle through the internet using the websocket protocol; and
the transit event broadcaster broadcasts the notification of the transit event to the respective at least one other vehicle through the websocket for the other vehicle.
14. A vehicle device that broadcasts localized transit events detected during transit of a vehicle, the vehicle device comprising:
a processor;
a location detector that detects a location of the vehicle;
a transit service communicator that communicates with a transit service;
a transit event detector that detects a transit event in the location of the vehicle; and
a memory storing instructions that, when executed on the processor, cause the vehicle device to provide a system comprising:
a transit service interface that:
transmits the location, via the transit service communicator, to add the vehicle to a vehicle area group for the location, and
transmits, via the transit service communicator, the transit event for broadcasting to other vehicles of the vehicle area group; and
a local event notifier that, upon receiving from the transit service a notification of a transit event for the vehicle area group, utilizes the notification in the transit of the vehicle.
15. The vehicle device of claim 14 , wherein:
the transit service communicator further comprises an internet connection through which the transit service communicator communicates with the transit service using a websocket protocol; and
the local event notifier receives the notification from the transit service through a websocket of the websocket protocol allocated to communicate with the transit service.
16. The vehicle device of claim 14 , wherein the transit event detector further comprises:
a proximity sensor that generates proximity data indicating a proximity of the vehicle to a second vehicle; and
a proximity data evaluator that evaluates the proximity data to identify the transit event.
17. The vehicle device of claim 14 , wherein the transit event detector further comprises: a localized broadcast channel monitor that receives a notification of a localized transit event over a localized broadcast messaging channel.
18. The vehicle device of claim 17 , wherein the transit service interface transmits, via the transit service communicator, the notification of the localized transit event received over the localized broadcast messaging channel.
19. The vehicle device of claim 14 , wherein the system further comprises: a local transit event rebroadcaster that locally rebroadcasts the notification of the transit event over a localized broadcast messaging channel.
20. The vehicle device of claim 14 , wherein:
the vehicle is in communication with a second vehicle of the location through a local vehicle communicator; and
the system further comprises: a local transit event notifier that transmits the notification of the transit event to the second vehicle through the local vehicle communication.
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Cited By (60)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20170012812A1 (en) * | 2015-07-07 | 2017-01-12 | International Business Machines Corporation | Management of events and moving objects |
US20170213461A1 (en) * | 2016-01-21 | 2017-07-27 | Ford Global Technologies, Llc | System and method for vehicle group communication via dedicated short range communication |
US20180005460A1 (en) * | 2016-06-29 | 2018-01-04 | Volkswagen Ag | Method for spectrally efficient determination of collective environmental information for cooperative and/or autonomous driving |
US20180107445A1 (en) * | 2015-03-31 | 2018-04-19 | Sony Corporation | Information processing device, control method, and program |
US10043323B1 (en) * | 2014-05-20 | 2018-08-07 | State Farm Mutual Automotive Insurance Company | Accident response using autonomous vehicle monitoring |
US10048683B2 (en) * | 2015-11-04 | 2018-08-14 | Zoox, Inc. | Machine learning systems and techniques to optimize teleoperation and/or planner decisions |
US20180276974A1 (en) * | 2017-03-21 | 2018-09-27 | GM Global Technology Operations LLC | Automatic transmission of reminders for devices left behind |
US20180286244A1 (en) * | 2017-03-31 | 2018-10-04 | T-Mobile U.S.A., Inc. | Managing communications between connected vehicles via a cellular network |
WO2018183950A1 (en) * | 2017-03-31 | 2018-10-04 | T-Mobile Usa, Inc. | Managing communications between connected vehicles via a cellular network |
US20180286245A1 (en) * | 2017-03-31 | 2018-10-04 | T-Mobile U.S.A., Inc. | Managing communications for connected vehicles using a cellular network |
US20180299283A1 (en) * | 2017-04-17 | 2018-10-18 | Ford Global Technologies, Llc | Vehicle Route Control |
US10134278B1 (en) | 2016-01-22 | 2018-11-20 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle application |
US20180356821A1 (en) * | 2015-11-04 | 2018-12-13 | Zoox, Inc. | Coordination of dispatching and maintaining fleet of autonomous vehicles |
US10157423B1 (en) | 2014-11-13 | 2018-12-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating style and mode monitoring |
US10156848B1 (en) | 2016-01-22 | 2018-12-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle routing during emergencies |
US10168424B1 (en) | 2017-06-21 | 2019-01-01 | International Business Machines Corporation | Management of mobile objects |
US20190043358A1 (en) * | 2016-02-03 | 2019-02-07 | Volkswagen Aktiengesellschaft | Methods, devices, and computer programs for providing information about a dangerous situation on a vehicle-to-vehicle interface |
US10248119B2 (en) | 2015-11-04 | 2019-04-02 | Zoox, Inc. | Interactive autonomous vehicle command controller |
DE102017218091A1 (en) * | 2017-10-11 | 2019-04-11 | Bayerische Motoren Werke Aktiengesellschaft | Method and device for updating traffic information |
US10262529B2 (en) | 2015-06-19 | 2019-04-16 | International Business Machines Corporation | Management of moving objects |
US10324463B1 (en) | 2016-01-22 | 2019-06-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation adjustment based upon route |
US10334050B2 (en) | 2015-11-04 | 2019-06-25 | Zoox, Inc. | Software application and logic to modify configuration of an autonomous vehicle |
US10339810B2 (en) | 2017-06-21 | 2019-07-02 | International Business Machines Corporation | Management of mobile objects |
US10373259B1 (en) | 2014-05-20 | 2019-08-06 | State Farm Mutual Automobile Insurance Company | Fully autonomous vehicle insurance pricing |
US10395332B1 (en) | 2016-01-22 | 2019-08-27 | State Farm Mutual Automobile Insurance Company | Coordinated autonomous vehicle automatic area scanning |
US10401852B2 (en) | 2015-11-04 | 2019-09-03 | Zoox, Inc. | Teleoperation system and method for trajectory modification of autonomous vehicles |
US10446037B2 (en) | 2015-11-04 | 2019-10-15 | Zoox, Inc. | Software application to request and control an autonomous vehicle service |
US10475127B1 (en) | 2014-07-21 | 2019-11-12 | State Farm Mutual Automobile Insurance Company | Methods of providing insurance savings based upon telematics and insurance incentives |
US10498685B2 (en) * | 2017-11-20 | 2019-12-03 | Google Llc | Systems, methods, and apparatus for controlling provisioning of notifications based on sources of the notifications |
US10504368B2 (en) | 2017-06-21 | 2019-12-10 | International Business Machines Corporation | Management of mobile objects |
US10540895B2 (en) | 2017-06-21 | 2020-01-21 | International Business Machines Corporation | Management of mobile objects |
US10546488B2 (en) | 2017-06-21 | 2020-01-28 | International Business Machines Corporation | Management of mobile objects |
US20200051427A1 (en) * | 2018-08-10 | 2020-02-13 | Honda Motor Co.,Ltd. | Control device and computer readable storage medium |
US10600322B2 (en) | 2017-06-21 | 2020-03-24 | International Business Machines Corporation | Management of mobile objects |
WO2020089039A1 (en) * | 2018-10-29 | 2020-05-07 | Robert Bosch Gmbh | Method for the vehicle-based verification of at least one detected dangerous place |
US10712750B2 (en) | 2015-11-04 | 2020-07-14 | Zoox, Inc. | Autonomous vehicle fleet service and system |
US10719886B1 (en) | 2014-05-20 | 2020-07-21 | State Farm Mutual Automobile Insurance Company | Accident fault determination for autonomous vehicles |
US10748419B1 (en) | 2015-08-28 | 2020-08-18 | State Farm Mutual Automobile Insurance Company | Vehicular traffic alerts for avoidance of abnormal traffic conditions |
US20210225092A1 (en) * | 2020-01-16 | 2021-07-22 | Ford Global Technologies, Llc | Method and apparatus for one to many vehicle broadcast handling |
US11106218B2 (en) | 2015-11-04 | 2021-08-31 | Zoox, Inc. | Adaptive mapping to navigate autonomous vehicles responsive to physical environment changes |
US11138418B2 (en) | 2018-08-06 | 2021-10-05 | Gal Zuckerman | Systems and methods for tracking persons by utilizing imagery data captured by on-road vehicles |
US11151883B2 (en) * | 2017-11-03 | 2021-10-19 | International Business Machines Corporation | Empathic autonomous vehicle |
US11206375B2 (en) | 2018-03-28 | 2021-12-21 | Gal Zuckerman | Analyzing past events by utilizing imagery data captured by a plurality of on-road vehicles |
US11242051B1 (en) | 2016-01-22 | 2022-02-08 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle action communications |
US11273283B2 (en) | 2017-12-31 | 2022-03-15 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement to enhance emotional response |
US11283877B2 (en) | 2015-11-04 | 2022-03-22 | Zoox, Inc. | Software application and logic to modify configuration of an autonomous vehicle |
US11301767B2 (en) | 2015-11-04 | 2022-04-12 | Zoox, Inc. | Automated extraction of semantic information to enhance incremental mapping modifications for robotic vehicles |
US11364361B2 (en) | 2018-04-20 | 2022-06-21 | Neuroenhancement Lab, LLC | System and method for inducing sleep by transplanting mental states |
US11441916B1 (en) | 2016-01-22 | 2022-09-13 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle trip routing |
US11452839B2 (en) | 2018-09-14 | 2022-09-27 | Neuroenhancement Lab, LLC | System and method of improving sleep |
US11474518B2 (en) * | 2019-05-13 | 2022-10-18 | International Business Machines Corporation | Event validation using multiple sources |
US20230045241A1 (en) * | 2021-08-03 | 2023-02-09 | GM Global Technology Operations LLC | Remote observation and reporting of vehicle operating condition via v2x communication |
US11580604B1 (en) | 2014-05-20 | 2023-02-14 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US11610493B1 (en) * | 2016-03-22 | 2023-03-21 | Amazon Technologies, Inc. | Unmanned aerial vehicles utilized to collect updated travel related data for deliveries |
US11669090B2 (en) | 2014-05-20 | 2023-06-06 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US11669071B2 (en) | 2020-01-08 | 2023-06-06 | International Business Machines Corporation | Organizing a temporary device group for collaborative computing |
US11719545B2 (en) | 2016-01-22 | 2023-08-08 | Hyundai Motor Company | Autonomous vehicle component damage and salvage assessment |
US11717686B2 (en) | 2017-12-04 | 2023-08-08 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement to facilitate learning and performance |
US11723579B2 (en) | 2017-09-19 | 2023-08-15 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement |
DE102022206506A1 (en) | 2022-06-28 | 2023-12-28 | Volkswagen Aktiengesellschaft | Method for setting up a virtual ad hoc network and central data processing device |
Families Citing this family (386)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10118576B2 (en) | 2002-06-11 | 2018-11-06 | Intelligent Technologies International, Inc. | Shipping container information recordation techniques |
US9701265B2 (en) | 2002-06-11 | 2017-07-11 | Intelligent Technologies International, Inc. | Smartphone-based vehicle control methods |
US9562776B2 (en) | 2013-04-23 | 2017-02-07 | Intelligent Mechatronic Systems Inc. | Location-based security |
US20210009136A1 (en) * | 2014-03-03 | 2021-01-14 | Inrix, Inc. | Presenting geographic search results using location projection and time windows |
US10692370B2 (en) * | 2014-03-03 | 2020-06-23 | Inrix, Inc. | Traffic obstruction detection |
US9623878B2 (en) | 2014-04-02 | 2017-04-18 | Magna Electronics Inc. | Personalized driver assistance system for vehicle |
JP6187370B2 (en) * | 2014-04-10 | 2017-08-30 | トヨタ自動車株式会社 | Driving behavior classification device and driving behavior classification method |
US20160179062A1 (en) * | 2014-12-17 | 2016-06-23 | Caterpillar Inc. | Machine data management system using removable controller |
US10025996B2 (en) * | 2014-12-22 | 2018-07-17 | Volkswagen Ag | Early detection of exit only and shared lanes using perception technology |
US10367869B2 (en) * | 2014-12-30 | 2019-07-30 | Ford Global Technologies, Llc | Remote vehicle control and operation |
JP6315827B2 (en) * | 2015-03-27 | 2018-04-25 | 国立大学法人名古屋大学 | Driving assistance device |
US11482100B2 (en) * | 2015-03-28 | 2022-10-25 | Intel Corporation | Technologies for detection of anomalies in vehicle traffic patterns |
EP3281020B1 (en) | 2015-04-09 | 2022-05-04 | Appy Risk Technologies Limited | Opportunistic calibration of a smartphone orientation in a vehicle |
ES2624498T3 (en) * | 2015-04-18 | 2017-07-14 | Urban Software Institute GmbH | System and method for message routing |
US10077056B1 (en) | 2015-04-24 | 2018-09-18 | State Farm Mutual Automobile Insurance Company | Managing self-driving behavior of autonomous or semi-autonomous vehicle based upon actual driving behavior of driver |
WO2016177437A1 (en) * | 2015-05-05 | 2016-11-10 | Balabit S.A. | Computer-implemented method for determining computer system security threats, security operations center system and computer program product |
US9616773B2 (en) | 2015-05-11 | 2017-04-11 | Uber Technologies, Inc. | Detecting objects within a vehicle in connection with a service |
US9842437B2 (en) * | 2015-06-29 | 2017-12-12 | Allstate Insurance Company | Automatically identifying drivers |
GB201512490D0 (en) | 2015-07-16 | 2015-08-19 | Tomtom Traffic Bv | Methods and systems for detecting a closure of a navigable element |
KR102135088B1 (en) * | 2015-07-20 | 2020-07-17 | 엘지전자 주식회사 | Autonomous Driving Vehicle |
WO2017017761A1 (en) * | 2015-07-27 | 2017-02-02 | 日産自動車株式会社 | Route guidance device and route guidance method |
US10691958B1 (en) * | 2015-07-30 | 2020-06-23 | Ambarella International Lp | Per-lane traffic data collection and/or navigation |
KR20170015114A (en) * | 2015-07-30 | 2017-02-08 | 삼성전자주식회사 | Autonomous vehicle and method for controlling the autonomous vehicle |
CN108028015B (en) * | 2015-09-18 | 2021-07-23 | 索尼公司 | Information processing apparatus, information processing method, and storage medium |
US9958870B1 (en) | 2015-09-29 | 2018-05-01 | Amazon Technologies, Inc. | Environmental condition identification assistance for autonomous vehicles |
US9971348B1 (en) * | 2015-09-29 | 2018-05-15 | Amazon Technologies, Inc. | Passenger profiles for autonomous vehicles |
US10558718B2 (en) * | 2015-11-03 | 2020-02-11 | Dell Products, Lp | Systems and methods for website improvement |
DE102016200759B4 (en) * | 2015-11-12 | 2023-03-30 | Volkswagen Aktiengesellschaft | Method, device and processing device for controlling functions in a vehicle |
CN107010073A (en) * | 2015-11-30 | 2017-08-04 | 法拉第未来公司 | System and method based on the occupancy condition in data aggregate automatic detection vehicle |
US10712160B2 (en) | 2015-12-10 | 2020-07-14 | Uatc, Llc | Vehicle traction map for autonomous vehicles |
US20170168487A1 (en) * | 2015-12-11 | 2017-06-15 | International Business Machines Corporation | System and method for tracking pollution |
US9841763B1 (en) | 2015-12-16 | 2017-12-12 | Uber Technologies, Inc. | Predictive sensor array configuration system for an autonomous vehicle |
US9840256B1 (en) | 2015-12-16 | 2017-12-12 | Uber Technologies, Inc. | Predictive sensor array configuration system for an autonomous vehicle |
US20170174221A1 (en) * | 2015-12-18 | 2017-06-22 | Robert Lawson Vaughn | Managing autonomous vehicles |
US10246065B2 (en) | 2015-12-29 | 2019-04-02 | Thunder Power New Energy Vehicle Development Company Limited | Vehicle hazard detection and warning system |
US10479373B2 (en) * | 2016-01-06 | 2019-11-19 | GM Global Technology Operations LLC | Determining driver intention at traffic intersections for automotive crash avoidance |
US10460600B2 (en) * | 2016-01-11 | 2019-10-29 | NetraDyne, Inc. | Driver behavior monitoring |
US9956956B2 (en) * | 2016-01-11 | 2018-05-01 | Denso Corporation | Adaptive driving system |
KR102500838B1 (en) * | 2016-01-11 | 2023-02-16 | 한화테크윈 주식회사 | Method of providing path based on surveillance zone and apparatus for the same |
US10165171B2 (en) | 2016-01-22 | 2018-12-25 | Coban Technologies, Inc. | Systems, apparatuses, and methods for controlling audiovisual apparatuses |
EP3405932A1 (en) * | 2016-01-29 | 2018-11-28 | KiwiSecurity Software GmbH | Methods and apparatus for using video analytics to detect regions for privacy protection within images from moving cameras |
US9937923B2 (en) * | 2016-01-30 | 2018-04-10 | Bendix Commercial Vehicle Systems Llc | System and method for providing a speed warning and speed control |
CN105679021B (en) * | 2016-02-02 | 2018-11-06 | 招商局重庆交通科研设计院有限公司 | Journey time fusion forecasting and querying method based on traffic big data |
US9672738B1 (en) * | 2016-02-02 | 2017-06-06 | Allstate Insurance Company | Designing preferred vehicle routes based on driving scores from other vehicles |
US10037031B2 (en) * | 2016-02-05 | 2018-07-31 | Ford Global Technologies, Llc | Vehicle operation states |
GB201604159D0 (en) * | 2016-02-09 | 2016-04-27 | Tomtom Traffic Bv | Methods and systems for identifying navigable elements affected by weather conditions |
DE102016202659B3 (en) * | 2016-02-22 | 2016-09-22 | Siemens Aktiengesellschaft | Method and device for providing recorded, anonymized routes |
US9823664B2 (en) | 2016-02-25 | 2017-11-21 | A.M.T.S., Llc | Unmanned aircraft for positioning an instrument for inspection purposes and methods of inspecting a target surface |
US9990548B2 (en) | 2016-03-09 | 2018-06-05 | Uber Technologies, Inc. | Traffic signal analysis system |
EP3217400B1 (en) * | 2016-03-10 | 2018-11-07 | Philips Lighting Holding B.V. | Pollution estimation system |
US10160340B2 (en) * | 2016-03-16 | 2018-12-25 | GM Global Technology Operations LLC | Adaptive system and method for optimizing battery life in a plug-in vehicle |
NO341488B1 (en) * | 2016-04-05 | 2017-11-27 | Apace Resources As | System for controlling traffic |
US10334395B2 (en) | 2016-04-07 | 2019-06-25 | Vizsafe, Inc. | Targeting individuals based on their location and distributing geo-aware channels or categories to them and requesting information therefrom |
US10484724B2 (en) * | 2016-04-07 | 2019-11-19 | Vizsafe, Inc. | Viewing and streaming live cameras to users near their location as indicated on a map or automatically based on a geofence or location boundary |
US10019904B1 (en) | 2016-04-11 | 2018-07-10 | State Farm Mutual Automobile Insurance Company | System for identifying high risk parking lots |
US10222228B1 (en) | 2016-04-11 | 2019-03-05 | State Farm Mutual Automobile Insurance Company | System for driver's education |
US10872379B1 (en) | 2016-04-11 | 2020-12-22 | State Farm Mutual Automobile Insurance Company | Collision risk-based engagement and disengagement of autonomous control of a vehicle |
US10247565B2 (en) | 2016-04-11 | 2019-04-02 | State Farm Mutual Automobile Insurance Company | Traffic risk avoidance for a route selection system |
US10486708B1 (en) * | 2016-04-11 | 2019-11-26 | State Farm Mutual Automobile Insurance Company | System for adjusting autonomous vehicle driving behavior to mimic that of neighboring/surrounding vehicles |
US10571283B1 (en) | 2016-04-11 | 2020-02-25 | State Farm Mutual Automobile Insurance Company | System for reducing vehicle collisions based on an automated segmented assessment of a collision risk |
US10026309B1 (en) | 2016-04-11 | 2018-07-17 | State Farm Mutual Automobile Insurance Company | Networked vehicle control systems to facilitate situational awareness of vehicles |
US11851041B1 (en) | 2016-04-11 | 2023-12-26 | State Farm Mutual Automobile Insurance Company | System for determining road slipperiness in bad weather conditions |
US10233679B1 (en) | 2016-04-11 | 2019-03-19 | State Farm Mutual Automobile Insurance Company | Systems and methods for control systems to facilitate situational awareness of a vehicle |
US9429947B1 (en) * | 2016-04-14 | 2016-08-30 | Eric John Wengreen | Self-driving vehicle systems and methods |
US10042055B2 (en) | 2016-04-20 | 2018-08-07 | Here Global B.V. | Traffic volume estimation |
US9953523B2 (en) | 2016-04-22 | 2018-04-24 | Here Global B.V. | Node-centric navigation optimization |
EP3236446B1 (en) | 2016-04-22 | 2022-04-13 | Volvo Car Corporation | Arrangement and method for providing adaptation to queue length for traffic light assist-applications |
US10370102B2 (en) | 2016-05-09 | 2019-08-06 | Coban Technologies, Inc. | Systems, apparatuses and methods for unmanned aerial vehicle |
US10152858B2 (en) | 2016-05-09 | 2018-12-11 | Coban Technologies, Inc. | Systems, apparatuses and methods for triggering actions based on data capture and characterization |
US10789840B2 (en) * | 2016-05-09 | 2020-09-29 | Coban Technologies, Inc. | Systems, apparatuses and methods for detecting driving behavior and triggering actions based on detected driving behavior |
US10088330B2 (en) * | 2016-05-12 | 2018-10-02 | Telenav, Inc. | Navigation system with notification mechanism and method of operation thereof |
US10202127B2 (en) * | 2016-05-19 | 2019-02-12 | Toyota Jidosha Kabushiki Kaisha | User profile-based automatic parameter tuning system for connected vehicles |
US20170345112A1 (en) * | 2016-05-25 | 2017-11-30 | Tyco Fire & Security Gmbh | Dynamic Threat Analysis Engine for Mobile Users |
US20170349184A1 (en) * | 2016-06-06 | 2017-12-07 | GM Global Technology Operations LLC | Speech-based group interactions in autonomous vehicles |
US10328935B2 (en) * | 2016-06-08 | 2019-06-25 | GM Global Technology Operations LLC | Adaptive cruise control system and method of operating the same |
CN106004735B (en) * | 2016-06-27 | 2019-03-15 | 京东方科技集团股份有限公司 | The method of adjustment of onboard system and vehicle service |
JP6550016B2 (en) * | 2016-06-27 | 2019-07-24 | 株式会社デンソー | Vehicle control apparatus and vehicle control method |
US10183679B2 (en) * | 2016-06-28 | 2019-01-22 | Volkswagen Aktiengesellschaft | Apparatus, system and method for personalized settings for driver assistance systems |
US10189482B2 (en) * | 2016-06-28 | 2019-01-29 | Volkswagen Aktiengesellschaft | Apparatus, system and method for personalized settings for driver assistance systems |
US20180005052A1 (en) | 2016-07-01 | 2018-01-04 | Uber Technologies, Inc. | Static object detection for operating autonomous vehicle |
US10818173B2 (en) * | 2016-07-06 | 2020-10-27 | Ford Global Technologies, Llc | Information sharing and user experience enhancement by context-aware vehicles |
US10162354B2 (en) | 2016-07-21 | 2018-12-25 | Baidu Usa Llc | Controlling error corrected planning methods for operating autonomous vehicles |
US10112611B2 (en) * | 2016-07-25 | 2018-10-30 | Toyota Motor Engineering & Manufacturing North America, Inc. | Adaptive vehicle control systems and methods of altering a condition of a vehicle using the same |
US11322018B2 (en) | 2016-07-31 | 2022-05-03 | NetraDyne, Inc. | Determining causation of traffic events and encouraging good driving behavior |
DE102016214822B4 (en) * | 2016-08-10 | 2022-06-09 | Audi Ag | Method for assisting a driver in driving a motor vehicle |
DE102016216701B4 (en) * | 2016-09-05 | 2020-01-02 | Audi Ag | Method for operating a support system for preventing a motor vehicle and motor vehicle from stopping |
US10093322B2 (en) * | 2016-09-15 | 2018-10-09 | International Business Machines Corporation | Automatically providing explanations for actions taken by a self-driving vehicle |
US9919648B1 (en) * | 2016-09-27 | 2018-03-20 | Robert D. Pedersen | Motor vehicle artificial intelligence expert system dangerous driving warning and control system and method |
US9931976B1 (en) | 2016-10-05 | 2018-04-03 | Dell Products L.P. | Truck safety zone using a vehicle gateway |
US10145700B2 (en) | 2016-10-05 | 2018-12-04 | Dell Products L.P. | Vehicle firmware update using a vehicle gateway |
US10673948B2 (en) | 2016-10-05 | 2020-06-02 | Dell Products L.P. | Trailer identification, inspection, and verification using a vehicle gateway |
US10315662B2 (en) | 2016-10-05 | 2019-06-11 | Dell Products L.P. | Determining a driver condition using a vehicle gateway |
US10402772B2 (en) | 2016-10-05 | 2019-09-03 | Dell Products L.P. | Cargo geofencing using a vehicle gateway |
US11119480B2 (en) * | 2016-10-20 | 2021-09-14 | Magna Electronics Inc. | Vehicle control system that learns different driving characteristics |
EP3316188A1 (en) * | 2016-10-28 | 2018-05-02 | Thomson Licensing LLC | Decision making method and system for providing service recommendation system |
KR20180051274A (en) * | 2016-11-08 | 2018-05-16 | 현대자동차주식회사 | Method for controlling driving of vehicle using driving information of front vehicle |
DE102016221873A1 (en) * | 2016-11-08 | 2018-05-09 | Bayerische Motoren Werke Aktiengesellschaft | Vehicle guidance depending on an occupant |
KR102003940B1 (en) | 2016-11-11 | 2019-10-01 | 엘지전자 주식회사 | Autonomous vehicle and control method thereof |
US10328913B2 (en) | 2016-11-18 | 2019-06-25 | International Business Machines Corporation | Facilitation of automatic adjustment of a braking system |
KR20180056084A (en) * | 2016-11-18 | 2018-05-28 | 현대자동차주식회사 | Vehicle and Controlling Method thereof |
US10338591B2 (en) | 2016-11-22 | 2019-07-02 | Amazon Technologies, Inc. | Methods for autonomously navigating across uncontrolled and controlled intersections |
WO2018097609A1 (en) | 2016-11-26 | 2018-05-31 | 팅크웨어(주) | Device, method, computer program and computer readable recording medium for route guidance |
CN116465424A (en) * | 2016-11-26 | 2023-07-21 | 星克跃尔株式会社 | Apparatus, method, computer program, and computer-readable recording medium for guiding route |
CN106407480B (en) * | 2016-11-29 | 2020-02-04 | 北京世纪高通科技有限公司 | Information query method and system |
CN110291477B (en) * | 2016-12-02 | 2022-08-16 | 嘉蒂克人工智能公司 | Vehicle control system and method of use |
DE102016224290B4 (en) * | 2016-12-06 | 2020-01-09 | Trw Automotive Gmbh | Process for computer-aided traffic monitoring of route sections of a road network |
US10274338B2 (en) * | 2016-12-11 | 2019-04-30 | International Business Machines Corporation | Risk situations for vehicle occupants based on data provided by vehicle sensors and contextual information |
KR20180069492A (en) * | 2016-12-15 | 2018-06-25 | 현대자동차주식회사 | Apparatus and Method for controlling Advanced Driver Assistance System |
CN106408139B (en) * | 2016-12-20 | 2019-08-06 | 中国人民解放军空军装备研究院雷达与电子对抗研究所 | Airport arrival rate prediction technique and device |
US10794711B2 (en) | 2016-12-30 | 2020-10-06 | DeepMap Inc. | High definition map updates based on sensor data collected by autonomous vehicles |
US10986515B2 (en) * | 2017-02-01 | 2021-04-20 | Veniam, Inc. | Systems and methods for context-aware and profile-based security in a network of moving things, for example including autonomous vehicles |
US10127814B2 (en) * | 2017-02-03 | 2018-11-13 | Ford Global Technologies, Llc | Advanced V2X event dissemination |
JP2018135069A (en) * | 2017-02-23 | 2018-08-30 | パナソニックIpマネジメント株式会社 | Information processing system, information processing method, and program |
US10328973B2 (en) | 2017-03-06 | 2019-06-25 | Ford Global Technologies, Llc | Assisting drivers with roadway lane changes |
US10209718B2 (en) | 2017-03-14 | 2019-02-19 | Starsky Robotics, Inc. | Vehicle sensor system and method of use |
US10250611B2 (en) * | 2017-03-14 | 2019-04-02 | Allstate Insurance Company | Authenticating drivers |
US10139831B2 (en) * | 2017-03-17 | 2018-11-27 | Denso International America, Inc. | Vehicle system and vehicle controller for controlling vehicle |
CN108665699B (en) * | 2017-03-30 | 2020-04-03 | 杭州海康威视数字技术股份有限公司 | Method and device for predicting vehicle appearance place |
JP7074125B2 (en) * | 2017-03-30 | 2022-05-24 | ソニーグループ株式会社 | Information processing equipment and information processing method |
US20180281784A1 (en) * | 2017-03-31 | 2018-10-04 | GM Global Technology Operations LLC | Using a driver profile to enhance vehicle-to-everything applications |
US20220012780A1 (en) | 2017-04-05 | 2022-01-13 | State Farm Mutual Automobile Insurance Company | Systems and methods for estimating vehicle value via blockchain |
US10527449B2 (en) | 2017-04-10 | 2020-01-07 | Microsoft Technology Licensing, Llc | Using major route decision points to select traffic cameras for display |
US11087267B1 (en) * | 2017-04-12 | 2021-08-10 | Wells Fargo Bank, N.A. | Configurable vehicle |
US11124139B2 (en) * | 2017-04-12 | 2021-09-21 | Kawasaki Jukogyo Kabushiki Kaisha | Vehicle conversation information output device and conversation information output method |
WO2018189841A1 (en) | 2017-04-12 | 2018-10-18 | 川崎重工業株式会社 | Dialog information output device and dialog information output method for vehicle |
DE112018001586T5 (en) * | 2017-04-27 | 2020-01-02 | Hitachi Automotive Systems, Ltd. | Vehicle control device |
CN110234542A (en) * | 2017-04-28 | 2019-09-13 | 深圳市元征科技股份有限公司 | A kind of control method for vehicle and vehicle |
US10323951B2 (en) * | 2017-05-11 | 2019-06-18 | General Motors Llc | Method of generating a navigation-based route for a vehicle |
US10279793B2 (en) | 2017-05-11 | 2019-05-07 | Honda Motor Co., Ltd. | Understanding driver awareness through brake behavior analysis |
US10493994B1 (en) | 2017-05-11 | 2019-12-03 | State Farm Mutual Automobile Insurance Company | Vehicle driver performance based on contextual changes and driver response |
US11354616B1 (en) | 2017-05-11 | 2022-06-07 | State Farm Mutual Automobile Insurance Company | Vehicle driver safety performance based on relativity |
US11282009B2 (en) | 2017-05-23 | 2022-03-22 | Uatc, Llc | Fleet utilization efficiency for on-demand transportation services |
EP3410382A1 (en) * | 2017-05-30 | 2018-12-05 | iOnRoad Technologies Ltd. | Dynamic adaptation of insurance policy for a vehicle according to a selected driving profile |
US11334216B2 (en) * | 2017-05-30 | 2022-05-17 | Palantir Technologies Inc. | Systems and methods for visually presenting geospatial information |
US10636293B2 (en) * | 2017-06-07 | 2020-04-28 | International Business Machines Corporation | Uncertainty modeling in traffic demand prediction |
US20180356817A1 (en) * | 2017-06-07 | 2018-12-13 | Uber Technologies, Inc. | System and Methods to Enable User Control of an Autonomous Vehicle |
AU2017417952A1 (en) * | 2017-06-09 | 2019-12-19 | Prannoy Roy | Predictive traffic management system |
US10365653B2 (en) * | 2017-06-12 | 2019-07-30 | GM Global Technology Operations LLC | Personalized autonomous vehicle ride characteristics |
US20170274908A1 (en) * | 2017-06-12 | 2017-09-28 | Xiaoning Huai | Personalize self-driving cars |
US10803536B1 (en) | 2017-06-13 | 2020-10-13 | Wells Fargo Bank, N.A. | Property hunting trip in an autonomous vehicle |
EP3416147B1 (en) * | 2017-06-13 | 2020-01-15 | Volvo Car Corporation | Method for providing drowsiness alerts in vehicles |
US10384602B1 (en) * | 2017-06-14 | 2019-08-20 | United Services Automobile Association | Systems and methods for detecting and reducing distracted driving |
KR102628790B1 (en) | 2017-06-20 | 2024-01-24 | 모셔널 에이디 엘엘씨 | Risk processing for vehicles having autonomous driving capabilities |
CN107230384B (en) * | 2017-06-21 | 2020-09-25 | 深圳市盛路物联通讯技术有限公司 | Parking guidance system and method based on expected parking duration and weather information |
US10416043B2 (en) | 2017-06-23 | 2019-09-17 | Paccar Inc | Speed optimality analysis for evaluating the optimality of a powertrain |
CN107331163A (en) * | 2017-06-30 | 2017-11-07 | 贵阳海信网络科技有限公司 | A kind of queue length computational methods and device |
US11106917B2 (en) * | 2017-07-04 | 2021-08-31 | Turing Video | Surveillance system with human-machine interface |
US20190011275A1 (en) * | 2017-07-06 | 2019-01-10 | Andrew Whinston | System and method for routing autonomous vehicles |
US11651316B2 (en) | 2017-07-14 | 2023-05-16 | Allstate Insurance Company | Controlling vehicles using contextual driver and/or rider data based on automatic passenger detection and mobility status |
US11590981B2 (en) | 2017-07-14 | 2023-02-28 | Allstate Insurance Company | Shared mobility service passenger matching based on passenger attributes |
US11928621B2 (en) | 2017-07-14 | 2024-03-12 | Allstate Insurance Company | Controlling vehicles using contextual driver and/or rider data based on automatic passenger detection and mobility status |
CN107195190B (en) * | 2017-07-19 | 2020-11-10 | 广东工业大学 | Road condition information sharing system |
JP6855968B2 (en) * | 2017-07-20 | 2021-04-07 | トヨタ自動車株式会社 | Information processing equipment, information processing methods and information processing systems |
CN107331164B (en) * | 2017-07-25 | 2018-08-28 | 中南大学 | A kind of prediction technique of freeway toll station entrance vehicle number |
US10380889B2 (en) * | 2017-07-31 | 2019-08-13 | Hewlett Packard Enterprise Development Lp | Determining car positions |
US10816975B2 (en) * | 2017-08-09 | 2020-10-27 | Toyota Motor Engineering & Manufacturing North America, Inc. | Autonomous acceleration profile feedback system |
CN107484139B (en) * | 2017-08-14 | 2019-10-18 | 北京邮电大学 | A kind of car networking Cooperative Localization Method and device based on geographical location information |
JP6561095B2 (en) * | 2017-09-01 | 2019-08-14 | 本田技研工業株式会社 | Replenishment recommendation system and method |
US11560177B1 (en) | 2017-09-13 | 2023-01-24 | State Farm Mutual Automobile Insurance Company | Real-time vehicle driver feedback based on analytics |
US11193780B2 (en) | 2017-09-19 | 2021-12-07 | Continental Automotive Systems, Inc. | Vehicle safety system and method for providing a recommended path |
US10783725B1 (en) | 2017-09-27 | 2020-09-22 | State Farm Mutual Automobile Insurance Company | Evaluating operator reliance on vehicle alerts |
WO2019068042A1 (en) | 2017-09-29 | 2019-04-04 | Netradyne Inc. | Multiple exposure event determination |
US10902336B2 (en) * | 2017-10-03 | 2021-01-26 | International Business Machines Corporation | Monitoring vehicular operation risk using sensing devices |
US10223601B1 (en) | 2017-10-12 | 2019-03-05 | Denso International America, Inc. | Synthetic traffic object generator |
WO2019075341A1 (en) | 2017-10-12 | 2019-04-18 | Netradyne Inc. | Detection of driving actions that mitigate risk |
US10670414B2 (en) * | 2017-10-20 | 2020-06-02 | Paypal, Inc. | Load balancing for map application route selection and output |
US10379535B2 (en) | 2017-10-24 | 2019-08-13 | Lear Corporation | Drowsiness sensing system |
DE102017219302A1 (en) * | 2017-10-27 | 2019-05-02 | Bayerische Motoren Werke Aktiengesellschaft | Method for reducing the risk potential in road traffic |
WO2019091568A1 (en) * | 2017-11-10 | 2019-05-16 | Bayerische Motoren Werke Aktiengesellschaft | Method and apparatus for determining a travel destination from user generated content |
DE102017220033A1 (en) * | 2017-11-10 | 2019-05-16 | Volkswagen Aktiengesellschaft | Method for vehicle navigation |
CN107886339A (en) * | 2017-11-15 | 2018-04-06 | 百度在线网络技术(北京)有限公司 | Method and apparatus for output information |
US10239452B1 (en) * | 2017-11-15 | 2019-03-26 | Ford Global Technologies, Llc | Minimizing false collision avoidance warnings |
US10836403B2 (en) | 2017-12-04 | 2020-11-17 | Lear Corporation | Distractedness sensing system |
CN111433566A (en) * | 2017-12-18 | 2020-07-17 | 智加科技公司 | Method and system for human-like driving lane planning in an autonomous vehicle |
JP7009972B2 (en) * | 2017-12-18 | 2022-01-26 | トヨタ自動車株式会社 | Server device and congestion identification method |
US11273836B2 (en) | 2017-12-18 | 2022-03-15 | Plusai, Inc. | Method and system for human-like driving lane planning in autonomous driving vehicles |
US11130497B2 (en) * | 2017-12-18 | 2021-09-28 | Plusai Limited | Method and system for ensemble vehicle control prediction in autonomous driving vehicles |
US20190185012A1 (en) | 2017-12-18 | 2019-06-20 | PlusAI Corp | Method and system for personalized motion planning in autonomous driving vehicles |
US10648826B2 (en) * | 2017-12-20 | 2020-05-12 | Mastercard International Incorporated | Providing stop recommendations based on a travel path and transaction data |
CN107945557B (en) * | 2017-12-21 | 2020-10-23 | 爱驰汽车有限公司 | Real-time road condition display method and device, computing equipment and computer storage medium |
JP6939534B2 (en) * | 2017-12-26 | 2021-09-22 | トヨタ自動車株式会社 | Vehicle allocation management device |
KR20190078996A (en) * | 2017-12-27 | 2019-07-05 | 삼성전자주식회사 | Electronic device for providing operation information of a vecicle and method for the same |
JP7035531B2 (en) * | 2017-12-28 | 2022-03-15 | トヨタ自動車株式会社 | Vehicle operation management system |
US11104353B2 (en) * | 2018-01-02 | 2021-08-31 | Telenav, Inc. | Computing system with autonomous operation mechanism and method of operation thereof |
US10780890B2 (en) | 2018-01-03 | 2020-09-22 | Toyota Research Institute, Inc. | Vehicle systems and methods for detecting and mitigating an incapacitated driver |
US11718303B2 (en) * | 2018-01-03 | 2023-08-08 | Toyota Research Institute, Inc. | Vehicles and methods for building vehicle profiles based on reactions created by surrounding vehicles |
US10274950B1 (en) | 2018-01-06 | 2019-04-30 | Drivent Technologies Inc. | Self-driving vehicle systems and methods |
US10299216B1 (en) | 2018-01-06 | 2019-05-21 | Eric John Wengreen | Self-driving vehicle actions in response to a low battery |
US10303181B1 (en) | 2018-11-29 | 2019-05-28 | Eric John Wengreen | Self-driving vehicle systems and methods |
US11073838B2 (en) | 2018-01-06 | 2021-07-27 | Drivent Llc | Self-driving vehicle systems and methods |
JP2019121320A (en) * | 2018-01-11 | 2019-07-22 | 株式会社小糸製作所 | Inter-vehicle communication system, vehicle system, illumination system for vehicle, and vehicle |
US11639183B2 (en) * | 2018-01-17 | 2023-05-02 | Mitsubishi Electric Corporation | Driving control device, driving control method, and computer readable medium |
US10733881B2 (en) | 2018-01-23 | 2020-08-04 | International Business Machines Corporation | Detection of vehicle queueing events on a road |
CN110085024A (en) * | 2018-01-26 | 2019-08-02 | 德尔福技术有限责任公司 | Traffic control system |
US20190236949A1 (en) * | 2018-01-26 | 2019-08-01 | Delphi Technologies, Llc | Traffic control system |
US10755111B2 (en) | 2018-01-29 | 2020-08-25 | Micron Technology, Inc. | Identifying suspicious entities using autonomous vehicles |
US10460185B2 (en) * | 2018-01-30 | 2019-10-29 | Toyota Motor Engineering & Manufacturing North America, Inc. | Roadside image tracking system |
CN108109380B (en) * | 2018-01-31 | 2020-12-15 | 迈锐数据(北京)有限公司 | System, method and device for detecting vehicle queuing length |
US10210409B1 (en) * | 2018-02-07 | 2019-02-19 | Lear Corporation | Seating system with occupant stimulation and sensing |
GB201802366D0 (en) * | 2018-02-14 | 2018-03-28 | Tom Tom Traffic B V | Methods and systems for generating taffic volumn or traffic density data |
US11059494B1 (en) | 2018-02-15 | 2021-07-13 | State Farm Mutual Automobile Insurance Company | System and method for transferring preferences for autonomous driving |
DE102018202623A1 (en) * | 2018-02-21 | 2019-09-12 | Bayerische Motoren Werke Aktiengesellschaft | System and method for automatic adjustment of vehicle functions |
KR102481487B1 (en) * | 2018-02-27 | 2022-12-27 | 삼성전자주식회사 | Autonomous driving apparatus and method thereof |
US11009876B2 (en) | 2018-03-14 | 2021-05-18 | Micron Technology, Inc. | Systems and methods for evaluating and sharing autonomous vehicle driving style information with proximate vehicles |
US11727794B2 (en) * | 2018-03-14 | 2023-08-15 | Micron Technology, Inc. | Systems and methods for evaluating and sharing human driving style information with proximate vehicles |
US10909494B2 (en) * | 2018-03-27 | 2021-02-02 | Accenture Global Solutions Limited | System for collaborative logistics using a collaborative logistics map and a knowledge graph |
CN108284838A (en) * | 2018-03-27 | 2018-07-17 | 杭州欧镭激光技术有限公司 | A kind of detecting system and detection method for detecting outside vehicle environmental information |
US10578456B2 (en) * | 2018-03-28 | 2020-03-03 | Intel Corporation | Safety enhanced computer assisted driving method and apparatus |
JP6612916B2 (en) * | 2018-03-29 | 2019-11-27 | 株式会社Subaru | Automatic driving integrated control device, automatic driving integrated control system, and vehicle control device |
US11550061B2 (en) * | 2018-04-11 | 2023-01-10 | Aurora Operations, Inc. | Control of autonomous vehicle based on environmental object classification determined using phase coherent LIDAR data |
US10997429B2 (en) | 2018-04-11 | 2021-05-04 | Micron Technology, Inc. | Determining autonomous vehicle status based on mapping of crowdsourced object data |
US10676085B2 (en) | 2018-04-11 | 2020-06-09 | Aurora Innovation, Inc. | Training machine learning model based on training instances with: training instance input based on autonomous vehicle sensor data, and training instance output based on additional vehicle sensor data |
US10739147B2 (en) | 2018-04-11 | 2020-08-11 | Toyota Jidosha Kabushiki Kaisha | Hierarchical route generation, provision, and selection |
US20190315342A1 (en) * | 2018-04-13 | 2019-10-17 | GM Global Technology Operations LLC | Preference adjustment of autonomous vehicle performance dynamics |
US11821741B2 (en) | 2018-04-17 | 2023-11-21 | Lp-Research Inc. | Stress map and vehicle navigation route |
US10867218B2 (en) | 2018-04-26 | 2020-12-15 | Lear Corporation | Biometric sensor fusion to classify vehicle passenger state |
US11092963B2 (en) * | 2018-04-27 | 2021-08-17 | Motional Ad Llc | Autonomous vehicle operation based on passenger-count |
US11334753B2 (en) | 2018-04-30 | 2022-05-17 | Uatc, Llc | Traffic signal state classification for autonomous vehicles |
US10979857B2 (en) | 2018-05-03 | 2021-04-13 | Curbside Inc. | Content conversion tracking based on location data |
WO2019216584A1 (en) * | 2018-05-07 | 2019-11-14 | Samsung Electronics Co., Ltd. | Method and electronic device for determining safety driving score |
KR102563708B1 (en) * | 2018-05-14 | 2023-08-09 | 주식회사 에이치엘클레무브 | Apparatus and method for alerting front vehicle start |
JP6994567B2 (en) * | 2018-05-15 | 2022-01-14 | 日立Astemo株式会社 | Vehicle control device |
CN108806282B (en) * | 2018-06-01 | 2020-09-04 | 浙江大学 | Lane group maximum queuing length estimation method based on sample travel time information |
US10922969B2 (en) * | 2018-06-04 | 2021-02-16 | GM Global Technology Operations LLC | Systems, methods and apparatuses for detecting elevated freeways to prevent engaging cruise features |
DE102018209191A1 (en) * | 2018-06-08 | 2019-12-12 | Volkswagen Aktiengesellschaft | Method and system for operating an automatic driving function in a vehicle |
JP7040306B2 (en) | 2018-06-13 | 2022-03-23 | トヨタ自動車株式会社 | A recording medium that records an operation evaluation device, an operation evaluation method, and an operation evaluation program. |
JP7040307B2 (en) * | 2018-06-13 | 2022-03-23 | トヨタ自動車株式会社 | A recording medium that records an operation evaluation device, an operation evaluation method, and an operation evaluation program. |
WO2018167749A2 (en) * | 2018-06-13 | 2018-09-20 | Universidad Técnica Particular De Loja | System and method for preventing accidents caused by the presence of objects on transport routes resulting from natural phenomena |
US11161518B2 (en) | 2018-06-15 | 2021-11-02 | Micron Technology, Inc. | Detecting road conditions based on braking event data received from vehicles |
CN108944740B (en) * | 2018-07-10 | 2022-04-29 | 深圳市斗索科技有限公司 | Vehicle control method and system |
US11169601B2 (en) * | 2018-07-12 | 2021-11-09 | Toyota Research Institute, Inc. | Methods and systems for determining teleoperating user intent via eye tracking |
US10909866B2 (en) * | 2018-07-20 | 2021-02-02 | Cybernet Systems Corp. | Autonomous transportation system and methods |
JP7351836B2 (en) * | 2018-07-24 | 2023-09-27 | フォルシアクラリオン・エレクトロニクス株式会社 | Information gathering device and control method |
WO2020023876A1 (en) | 2018-07-27 | 2020-01-30 | Class G Incorporated | Air traffic tolling system |
US10466057B1 (en) | 2018-07-30 | 2019-11-05 | Wesley Edward Schwie | Self-driving vehicle systems and methods |
US11293770B2 (en) | 2018-08-02 | 2022-04-05 | salesforces.com, Inc. | Geographic routing engine |
US10242571B1 (en) * | 2018-08-02 | 2019-03-26 | Mapanything, Inc. | Utilizing determined optimized time windows for precomputing optimal path matrices to reduce computer resource usage |
EP3842304A3 (en) * | 2018-08-14 | 2021-09-15 | Mobileye Vision Technologies Ltd. | Systems and methods for navigating with safe distances |
KR102485441B1 (en) * | 2018-09-03 | 2023-01-06 | 현대자동차주식회사 | Vehicle and vehicle system |
US20200082287A1 (en) * | 2018-09-10 | 2020-03-12 | Here Global B.V. | Method and apparatus for selecting a vehicle using a passenger-based driving profile |
US10493952B1 (en) | 2019-03-21 | 2019-12-03 | Drivent Llc | Self-driving vehicle systems and methods |
US10223844B1 (en) | 2018-09-18 | 2019-03-05 | Wesley Edward Schwie | Self-driving vehicle systems and methods |
US10289922B1 (en) | 2018-09-18 | 2019-05-14 | Eric John Wengreen | System for managing lost, mislaid, or abandoned property in a self-driving vehicle |
US10282625B1 (en) | 2018-10-01 | 2019-05-07 | Eric John Wengreen | Self-driving vehicle systems and methods |
US10479319B1 (en) | 2019-03-21 | 2019-11-19 | Drivent Llc | Self-driving vehicle systems and methods |
US10471804B1 (en) | 2018-09-18 | 2019-11-12 | Drivent Llc | Self-driving vehicle systems and methods |
US11181387B2 (en) * | 2018-09-27 | 2021-11-23 | International Business Machines Corporation | Dynamic routing system |
US11038895B2 (en) | 2018-09-28 | 2021-06-15 | Intel Corporation | Trust management mechanisms |
US11644833B2 (en) | 2018-10-01 | 2023-05-09 | Drivent Llc | Self-driving vehicle systems and methods |
US11221621B2 (en) | 2019-03-21 | 2022-01-11 | Drivent Llc | Self-driving vehicle systems and methods |
US10900792B2 (en) | 2018-10-22 | 2021-01-26 | Drivent Llc | Self-driving vehicle systems and methods |
US10832569B2 (en) | 2019-04-02 | 2020-11-10 | Drivent Llc | Vehicle detection systems |
US10794714B2 (en) | 2018-10-01 | 2020-10-06 | Drivent Llc | Self-driving vehicle systems and methods |
US11678252B2 (en) * | 2018-10-05 | 2023-06-13 | Huawei Technologies Co., Ltd. | Quality of service information notification to user equipment, users, and application server |
DE102018008045B4 (en) * | 2018-10-11 | 2020-07-23 | Daimler Ag | Method and device for controlling display content on an output means of a vehicle |
US10977882B1 (en) * | 2018-10-17 | 2021-04-13 | Lytx, Inc. | Driver health profile |
US11636353B2 (en) * | 2018-10-19 | 2023-04-25 | International Business Machines Corporation | Cognitive system for localized LIDAR pollution detection using autonomous vehicles |
US10890460B2 (en) * | 2018-10-19 | 2021-01-12 | International Business Machines Corporation | Navigation and location validation for optimizing vehicle-based transit systems |
US10240938B1 (en) | 2018-10-22 | 2019-03-26 | Drivent Technologies Inc. | Self-driving vehicle systems and methods |
US11648951B2 (en) | 2018-10-29 | 2023-05-16 | Motional Ad Llc | Systems and methods for controlling actuators based on load characteristics and passenger comfort |
GB2613740B (en) * | 2018-10-30 | 2023-12-06 | Motional Ad Llc | Redundancy in autonomous vehicles |
US10481606B1 (en) | 2018-11-01 | 2019-11-19 | Drivent Llc | Self-driving vehicle systems and methods |
US10286908B1 (en) | 2018-11-01 | 2019-05-14 | Eric John Wengreen | Self-driving vehicle systems and methods |
US11403492B2 (en) | 2018-11-02 | 2022-08-02 | Aurora Operations, Inc. | Generating labeled training instances for autonomous vehicles |
US11256263B2 (en) | 2018-11-02 | 2022-02-22 | Aurora Operations, Inc. | Generating targeted training instances for autonomous vehicles |
US11209821B2 (en) | 2018-11-02 | 2021-12-28 | Aurora Operations, Inc. | Labeling autonomous vehicle data |
US11163312B2 (en) | 2018-11-02 | 2021-11-02 | Aurora Operations, Inc. | Removable automotive LIDAR data collection POD |
US11829143B2 (en) | 2018-11-02 | 2023-11-28 | Aurora Operations, Inc. | Labeling autonomous vehicle data |
US11086319B2 (en) | 2018-11-02 | 2021-08-10 | Aurora Operations, Inc. | Generating testing instances for autonomous vehicles |
US10940870B1 (en) * | 2018-11-28 | 2021-03-09 | BlueOwl, LLC | Systems and methods for visualizing predicted driving risk |
US11021147B2 (en) | 2018-12-12 | 2021-06-01 | Toyota Research Institute, Inc. | Vehicles and methods for determining objects of driver focus |
US10692388B1 (en) | 2018-12-14 | 2020-06-23 | General Electric Company | Global environmental data and application methods for understanding engine health and maintenance |
US11433917B2 (en) * | 2018-12-28 | 2022-09-06 | Continental Autonomous Mobility US, LLC | System and method of human interface for recommended path |
CN110647789A (en) * | 2018-12-29 | 2020-01-03 | 北京奇虎科技有限公司 | Method and device for identifying position of traffic signal lamp |
WO2020133452A1 (en) * | 2018-12-29 | 2020-07-02 | 驭势科技(北京)有限公司 | Intelligent communication method and apparatus |
US11237565B2 (en) | 2019-01-03 | 2022-02-01 | International Business Machines Corporation | Optimal driving characteristic adjustment for autonomous vehicles |
KR20210113224A (en) * | 2019-01-04 | 2021-09-15 | 세렌스 오퍼레이팅 컴퍼니 | Methods and systems for improving the safety and flexibility of autonomous vehicles using voice interaction |
DE102019200935B4 (en) * | 2019-01-25 | 2020-10-01 | Audi Ag | Method for operating an autonomously moving road user |
US10796571B2 (en) * | 2019-01-31 | 2020-10-06 | StradVision, Inc. | Method and device for detecting emergency vehicles in real time and planning driving routes to cope with situations to be expected to be occurred by the emergency vehicles |
US10668930B1 (en) * | 2019-02-04 | 2020-06-02 | State Farm Mutual Automobile Insurance Company | Determining acceptable driving behavior based on vehicle specific characteristics |
US10377342B1 (en) | 2019-02-04 | 2019-08-13 | Drivent Technologies Inc. | Self-driving vehicle systems and methods |
US10744976B1 (en) | 2019-02-04 | 2020-08-18 | Drivent Llc | Self-driving vehicle systems and methods |
US11466994B2 (en) * | 2019-02-08 | 2022-10-11 | Uber Technologies, Inc. | Optimized issue reporting system |
US11790773B2 (en) | 2019-02-25 | 2023-10-17 | Quantifly Llc | Vehicle parking data collection system and method |
DE102019202581B4 (en) | 2019-02-26 | 2021-09-02 | Volkswagen Aktiengesellschaft | Method for operating a driver information system in an ego vehicle and driver information system |
DE102019202588A1 (en) * | 2019-02-26 | 2020-08-27 | Volkswagen Aktiengesellschaft | Method for operating a driver information system in an ego vehicle and driver information system |
US11443394B2 (en) * | 2019-03-22 | 2022-09-13 | International Business Machines Corporation | Blockchain based building action management |
CN109903563B (en) * | 2019-03-27 | 2021-08-17 | 武汉理工大学 | Secondary parking line position optimization system and method during mixed traveling of bus lane |
IT201900004795A1 (en) * | 2019-03-29 | 2020-09-29 | Fiat Ricerche | AUTOMATIC SPEED REGULATION OF A VEHICLE BASED ON THE DRIVER'S DRIVING BEHAVIOR |
US11341846B2 (en) | 2019-04-04 | 2022-05-24 | Geotab Inc. | Traffic analytics system for defining road networks |
US11403938B2 (en) | 2019-04-04 | 2022-08-02 | Geotab Inc. | Method for determining traffic metrics of a road network |
US10699564B1 (en) * | 2019-04-04 | 2020-06-30 | Geotab Inc. | Method for defining intersections using machine learning |
US11335189B2 (en) | 2019-04-04 | 2022-05-17 | Geotab Inc. | Method for defining road networks |
US11335191B2 (en) | 2019-04-04 | 2022-05-17 | Geotab Inc. | Intelligent telematics system for defining road networks |
EP3723063A1 (en) * | 2019-04-08 | 2020-10-14 | Ningbo Geely Automobile Research & Development Co. Ltd. | Understanding road signs |
EP3723062A1 (en) * | 2019-04-09 | 2020-10-14 | Siemens Aktiengesellschaft | Method and device for the computer-implemented routing of motor vehicles in a predetermined area |
US11450157B2 (en) * | 2019-04-14 | 2022-09-20 | Otonomo Technologies Ltd. | Method and system for bundling automotive data |
US11472291B2 (en) | 2019-04-25 | 2022-10-18 | Motional Ad Llc | Graphical user interface for display of autonomous vehicle behaviors |
GB2588983B (en) | 2019-04-25 | 2022-05-25 | Motional Ad Llc | Graphical user interface for display of autonomous vehicle behaviors |
CN110335459A (en) * | 2019-04-26 | 2019-10-15 | 同济大学 | The intersection queue length estimation method and device of low-permeability track of vehicle data |
JP7464240B2 (en) * | 2019-04-26 | 2024-04-09 | Necソリューションイノベータ株式会社 | Prediction model generation device, travel suitability prediction device, prediction model production method, travel suitability prediction method, program and recording medium |
CN110001654B (en) * | 2019-05-06 | 2023-07-28 | 吉林大学 | Intelligent vehicle longitudinal speed tracking control system and control method for self-adaptive driver type |
CN110136437B (en) * | 2019-05-14 | 2021-03-19 | 青岛海信网络科技股份有限公司 | Method and device for determining left-right interference problem of intersection entrance lane |
KR102061750B1 (en) * | 2019-05-15 | 2020-01-03 | 주식회사 라이드플럭스 | Method and apparatus for controlling a vehicle’s driving operation using advance information |
US11485374B2 (en) * | 2019-05-21 | 2022-11-01 | Pony Ai Inc. | System and method for evacuation of a vehicle in condition |
CN110263378A (en) * | 2019-05-22 | 2019-09-20 | 北京汽车股份有限公司 | Wiper big data analysis method and apparatus, storage medium |
US11374768B2 (en) * | 2019-06-11 | 2022-06-28 | Mastercard International Incorporated | Method and system for real-time driving alerts |
CN110365746A (en) * | 2019-06-24 | 2019-10-22 | 广州艾帝西信息科技有限公司 | A kind of information transferring method and system |
DE102019209487A1 (en) * | 2019-06-28 | 2020-12-31 | Volkswagen Aktiengesellschaft | Process for anonymizing vehicle data |
US11422553B2 (en) * | 2019-06-28 | 2022-08-23 | Intel Corporation | Methods and apparatus to adjust autonomous vehicle driving software using machine programming |
CN110456807B (en) * | 2019-07-02 | 2021-01-12 | 西北工业大学 | Multi-spacecraft consistency dynamic gain control method |
US11524691B2 (en) | 2019-07-29 | 2022-12-13 | Lear Corporation | System and method for controlling an interior environmental condition in a vehicle |
US11295098B1 (en) * | 2019-07-29 | 2022-04-05 | Dev Kumar Thappla | Smart driver card device and driver data and traffic management system |
KR102135256B1 (en) * | 2019-08-08 | 2020-07-17 | 엘지전자 주식회사 | Method for user authentication of vehicle in autonomous driving system and apparatus thereof |
CN110610133A (en) * | 2019-08-09 | 2019-12-24 | 合肥京东方车载显示技术有限公司 | Vehicle communication method and device and terminal equipment |
US11100801B2 (en) * | 2019-08-12 | 2021-08-24 | Toyota Motor North America, Inc. | Utilizing sensors to detect hazard from other vehicle while driving |
CN112389451A (en) * | 2019-08-14 | 2021-02-23 | 大众汽车(中国)投资有限公司 | Method, device, medium, and vehicle for providing a personalized driving experience |
US11474530B1 (en) | 2019-08-15 | 2022-10-18 | Amazon Technologies, Inc. | Semantic navigation of autonomous ground vehicles |
CN114341962A (en) * | 2019-08-29 | 2022-04-12 | 三洋电机株式会社 | Dangerous vehicle display system, dangerous vehicle display device, dangerous vehicle display program, computer-readable recording medium, and apparatus having recorded the program |
US11572067B2 (en) | 2019-08-30 | 2023-02-07 | 7980302 Canada Inc. | Using ISA system to decelerate truck upon entering geofenced area |
US10957189B1 (en) * | 2019-09-09 | 2021-03-23 | GM Global Technology Operations LLC | Automatic vehicle alert and reporting systems and methods |
CN110766939B (en) * | 2019-09-20 | 2020-11-06 | 重庆交通大学 | Signalized intersection queuing length estimation method based on vehicle track data |
DE102019214476A1 (en) * | 2019-09-23 | 2021-03-25 | Siemens Mobility GmbH | Data connection operating method, data transmission unit and vehicle with data transmission unit |
US20210094565A1 (en) * | 2019-09-30 | 2021-04-01 | Ghost Locomotion Inc. | Motion-based scene selection for an autonomous vehicle |
US20210101618A1 (en) * | 2019-10-02 | 2021-04-08 | Upstream Security, Ltd. | System and method for connected vehicle risk detection |
US11501637B2 (en) * | 2019-10-04 | 2022-11-15 | Here Global B.V. | Method, apparatus, and system for detecting lane-level slowdown events |
US11545035B2 (en) * | 2019-11-15 | 2023-01-03 | Toyota Motor Engineering & Manufacturing North America, Inc. | Driver notification system |
CN110930698B (en) * | 2019-11-18 | 2021-05-04 | 北京交通大学 | Front road transparent calculation method under 5G Internet of vehicles environment |
US11636405B2 (en) | 2019-11-20 | 2023-04-25 | Here Global B.V. | Method, apparatus and computer program product for vehicle platooning |
US20210148716A1 (en) * | 2019-11-20 | 2021-05-20 | Here Global B.V. | Method, apparatus and computer program product for vehicle platooning |
US10966069B1 (en) * | 2019-12-02 | 2021-03-30 | Toyota Motor Engineering & Manufacturing North America, Inc. | Systems and methods for HD map generation using an edge server network |
US11521487B2 (en) * | 2019-12-09 | 2022-12-06 | Here Global B.V. | System and method to generate traffic congestion estimation data for calculation of traffic condition in a region |
CN110901646B (en) * | 2019-12-11 | 2021-08-31 | 北京小马慧行科技有限公司 | Vehicle control method, control device, storage medium, and processor |
US11781881B2 (en) | 2019-12-12 | 2023-10-10 | Toyota Motor Engineering & Manufacturing North America, Inc. | Methods and apparatus of vehicle guidance |
GB201918833D0 (en) * | 2019-12-19 | 2020-02-05 | Tomtom Traffic Bv | Methods and systems for generating traffic volume data |
US11450205B2 (en) * | 2019-12-31 | 2022-09-20 | Zoox, Inc. | Emergency vehicle detection and response |
US11915115B2 (en) | 2019-12-31 | 2024-02-27 | Google Llc | Lane selection using machine learning |
US11414088B2 (en) * | 2020-01-16 | 2022-08-16 | Toyota Motor Engineering & Manufacturing North America, Inc. | Anomalous driver detection system |
JP7140154B2 (en) * | 2020-03-04 | 2022-09-21 | トヨタ自動車株式会社 | vehicle controller |
US11187551B2 (en) * | 2020-03-10 | 2021-11-30 | International Business Machines Corporation | Methods and systems for recommending activities to users onboard vehicles |
US11433897B2 (en) * | 2020-03-13 | 2022-09-06 | GM Global Technology Operations LLC | Method and apparatus for determination of optimal cruising lane in an assisted driving system |
EP3913551A1 (en) * | 2020-05-19 | 2021-11-24 | GEOTAB Inc. | Method for defining road networks |
US11526711B1 (en) * | 2020-05-20 | 2022-12-13 | State Farm Mutual Automobile Insurance Company | Synchronizing image data with either vehicle telematics data or infrastructure data pertaining to a road segment |
US11571969B2 (en) * | 2020-06-04 | 2023-02-07 | Toyota Motor Engineering & Manufacturing North America, Inc. | External communication suppression device for driving automation |
CN111432347B (en) * | 2020-06-11 | 2020-09-08 | 腾讯科技(深圳)有限公司 | Information processing method, information processing apparatus, storage medium, and electronic device |
US11702083B2 (en) | 2020-06-11 | 2023-07-18 | 7980302 Canada Inc. | Using ISA system to implement a speed policy identified based on profile of a driving instance |
EP3932699A1 (en) | 2020-07-03 | 2022-01-05 | Webfleet Solutions B.V. | Tyre selection method and system |
CN113934203A (en) * | 2020-07-09 | 2022-01-14 | 奥迪股份公司 | Method, apparatus and storage medium for controlling autonomous vehicle |
US11393336B2 (en) * | 2020-08-10 | 2022-07-19 | International Business Machines Corporation | Smog analysis via digital computing platforms |
US11654919B2 (en) * | 2020-08-11 | 2023-05-23 | Aptiv Technologies Limited | Adaptive user-specific automated driver assistance system warnings |
US11613271B2 (en) * | 2020-08-18 | 2023-03-28 | Allstate Insurance Company | Driver behavior tracking and prediction |
US11749105B2 (en) * | 2020-10-01 | 2023-09-05 | Magna Electronics Inc. | Vehicular communication system with turn signal identification |
JP7363734B2 (en) | 2020-10-02 | 2023-10-18 | トヨタ自動車株式会社 | Traffic management system, traffic management method, and traffic management program |
CN112158201B (en) * | 2020-10-12 | 2021-08-10 | 北京信息职业技术学院 | Intelligent driving vehicle transverse control method and system |
KR20230093275A (en) * | 2020-10-14 | 2023-06-27 | 우이시 (상하이) 오토모티브 테크놀로지스 리미티드 | Traffic congestion detection method, device, electronic device and storage medium |
US11709061B2 (en) | 2020-10-16 | 2023-07-25 | Argo AI, LLC | Systems and methods for multi-modal transfer capabilities for smart infrastructure |
JP7400688B2 (en) * | 2020-10-19 | 2023-12-19 | トヨタ自動車株式会社 | Display device and display method |
CN112269385B (en) * | 2020-10-23 | 2021-09-07 | 北京理工大学 | Cloud unmanned vehicle dynamics control system and method |
CN112450003A (en) * | 2020-11-17 | 2021-03-09 | 刘德 | Urban planning method based on volume rate control technology |
US20240046784A1 (en) * | 2020-12-04 | 2024-02-08 | Viavi Solutions Inc. | Distributed acoustic sensing of traffic |
CN112712712B (en) * | 2020-12-21 | 2022-05-20 | 阿波罗智联(北京)科技有限公司 | Method and device for determining vehicle queuing information, road side equipment and cloud control platform |
US11847914B2 (en) * | 2021-01-22 | 2023-12-19 | Ford Global Technologies, Llc | Air pollution detection and remediation systems and methods |
JP2022122777A (en) * | 2021-02-10 | 2022-08-23 | トヨタ自動車株式会社 | Information processing apparatus, information processing method, and program |
US11904855B2 (en) | 2021-02-12 | 2024-02-20 | Toyota Motor Engineering & Manufacturing North America, Inc. | Cooperative driving system and method |
US11615478B2 (en) | 2021-02-19 | 2023-03-28 | Allstate Insurance Company | Selectively shared vehicle-based telematics |
JP7415978B2 (en) * | 2021-02-22 | 2024-01-17 | トヨタ自動車株式会社 | Information processing device, program and information processing method |
JP2022139190A (en) * | 2021-03-11 | 2022-09-26 | 本田技研工業株式会社 | Drive support device and vehicle |
US11702098B2 (en) * | 2021-03-23 | 2023-07-18 | The Regents Of The University Of Michigan | Roadmanship systems and methods |
US11872985B2 (en) * | 2021-03-30 | 2024-01-16 | Toyota Motor Engineering & Manufacturing North America, Inc. | Determining a setting for a cruise control |
US11749108B2 (en) * | 2021-03-31 | 2023-09-05 | Honda Motor Co., Ltd. | System and method for lane level traffic state estimation |
DE102021206152A1 (en) | 2021-06-16 | 2022-12-22 | Volkswagen Aktiengesellschaft | Method for authenticating a user of a vehicle and vehicle |
US11851070B1 (en) * | 2021-07-13 | 2023-12-26 | Lytx, Inc. | Driver identification using geospatial information |
CN113568434B (en) * | 2021-08-26 | 2024-03-12 | 中国人民解放军空军军医大学 | Unmanned aerial vehicle flight control system |
TWI782695B (en) * | 2021-09-06 | 2022-11-01 | 致茂電子股份有限公司 | Dual sided optical detection system with fluorescence detection function |
CN114241756B (en) * | 2021-12-07 | 2023-03-31 | 中交第一公路勘察设计研究院有限公司 | Method and system for dynamically using hard road shoulder during construction of expressway |
CN114162068B (en) * | 2021-12-31 | 2023-12-15 | 阿维塔科技(重庆)有限公司 | Method and device for managing intelligent driving function of vehicle and vehicle |
DE102022000185A1 (en) * | 2022-01-18 | 2023-07-20 | Mercedes-Benz Group AG | Method for determining a user-specific driving profile for an automated driving of a vehicle |
US11776397B2 (en) * | 2022-02-03 | 2023-10-03 | Toyota Motor North America, Inc. | Emergency notifications for transports |
FR3133815A1 (en) * | 2022-03-23 | 2023-09-29 | Hypervisoul Group | METHOD FOR INCREASING THE TRANSPORT CAPACITY OF A ROAD FOR AUTOMATED CONNECTED VEHICLES |
US20230368670A1 (en) * | 2022-05-10 | 2023-11-16 | Qualcomm Incorporated | Techniques for detecting vulnerable road users |
FR3136579A1 (en) * | 2022-06-14 | 2023-12-15 | Psa Automobiles Sa | Method and device for controlling a system for indicating a speed limit of a vehicle based on air pollution information |
EP4303045A1 (en) * | 2022-07-05 | 2024-01-10 | AirLib Inc. | Vehicle cabin air quality management |
US20240035837A1 (en) * | 2022-07-29 | 2024-02-01 | Toyota Connected North America, Inc. | Vehicle carbon footprint management |
US20240070158A1 (en) * | 2022-08-31 | 2024-02-29 | Alfred R. Barber | Systems and methods for older driver/certified driver evaluation |
DE102022122780A1 (en) | 2022-09-08 | 2024-03-14 | Bayerische Motoren Werke Aktiengesellschaft | Device and method for safely activating vehicle functions in the vehicle |
CN115985124B (en) * | 2022-11-30 | 2024-02-06 | 禾多科技(北京)有限公司 | Vehicle running control method and device, storage medium and electronic device |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070050130A1 (en) * | 2005-08-26 | 2007-03-01 | Grimm Donald K | Speed limit advisor |
US20090287401A1 (en) * | 2008-05-19 | 2009-11-19 | Uri Levine | System and method for realtime community information exchange |
US20100007523A1 (en) * | 2008-07-08 | 2010-01-14 | Nuriel Hatav | Driver alert system |
US20100060480A1 (en) * | 2008-09-05 | 2010-03-11 | Gm Global Technology Operations, Inc. | Reliable Packet Delivery Protocol for Geocast Protocol in Disconnected Vehicular Ad Hoc Network |
US20100161195A1 (en) * | 2008-12-18 | 2010-06-24 | Gm Global Technology Operations, Inc. | Method and Apparatus for Speed-Limit Following Cruise Control |
US20110087433A1 (en) * | 2009-10-08 | 2011-04-14 | Honda Motor Co., Ltd. | Method of Dynamic Intersection Mapping |
US20120229301A1 (en) * | 2008-07-24 | 2012-09-13 | Cecil Wayne Hilton Goodwin | Driver initiated vehicle-to-vehicle anonymous warning device |
US8412413B1 (en) * | 2011-12-21 | 2013-04-02 | Delphi Technologies, Inc. | Vehicle windshield display with obstruction detection |
US20130131969A1 (en) * | 2005-09-22 | 2013-05-23 | Clayco Research Limited Liability Company | Device, system and method for controlling speed of a vehicle using a positional information device |
US20140039784A1 (en) * | 2012-07-31 | 2014-02-06 | Flatiron Apps LLC | System and method for hailing taxicabs |
Family Cites Families (284)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7164117B2 (en) * | 1992-05-05 | 2007-01-16 | Automotive Technologies International, Inc. | Vehicular restraint system control system and method using multiple optical imagers |
US5189621A (en) * | 1987-05-06 | 1993-02-23 | Hitachi, Ltd. | Electronic engine control apparatus |
FR2648905B1 (en) * | 1989-06-26 | 1994-06-17 | Est Ctre Etu Techn Equipement | DEVICE FOR ASSESSING THE BEHAVIOR OF ROAD USERS |
WO1993009511A1 (en) * | 1991-11-01 | 1993-05-13 | Motorola, Inc. | A vehicle route planning system |
US5465289A (en) | 1993-03-05 | 1995-11-07 | E-Systems, Inc. | Cellular based traffic sensor system |
US6317721B1 (en) * | 1995-04-10 | 2001-11-13 | Texas Instruments Incorporated | Transaction accounting of toll transactions in transponder systems |
US7110880B2 (en) * | 1997-10-22 | 2006-09-19 | Intelligent Technologies International, Inc. | Communication method and arrangement |
US7629899B2 (en) | 1997-10-22 | 2009-12-08 | Intelligent Technologies International, Inc. | Vehicular communication arrangement and method |
WO1997020433A1 (en) * | 1995-12-01 | 1997-06-05 | Southwest Research Institute | Methods and apparatus for traffic incident detection |
DE19606258C1 (en) | 1996-02-06 | 1997-04-30 | Mannesmann Ag | Vehicle autonomous traffic jam detection method |
US5878368A (en) | 1996-09-13 | 1999-03-02 | Magellan Dis, Inc. | Navigation system with user definable cost values |
US20020150050A1 (en) * | 1999-06-17 | 2002-10-17 | Nathanson Martin D. | Automotive telemetry protocol |
JPH11304518A (en) | 1998-04-22 | 1999-11-05 | Sanyo Electric Co Ltd | Navigation device |
DE19835979B4 (en) * | 1998-08-08 | 2005-01-05 | Daimlerchrysler Ag | Method for monitoring traffic conditions and vehicle inflow control in a road network |
DE19843395A1 (en) | 1998-09-22 | 2000-03-23 | Volkswagen Ag | Method for speed and / or distance control in motor vehicles |
US6177885B1 (en) | 1998-11-03 | 2001-01-23 | Esco Electronics, Inc. | System and method for detecting traffic anomalies |
US6542808B2 (en) * | 1999-03-08 | 2003-04-01 | Josef Mintz | Method and system for mapping traffic congestion |
US6401034B1 (en) * | 1999-09-02 | 2002-06-04 | Navigation Technologies Corp. | Method and system for finding intermediate destinations with a navigation system |
US6490519B1 (en) * | 1999-09-27 | 2002-12-03 | Decell, Inc. | Traffic monitoring system and methods for traffic monitoring and route guidance useful therewith |
JP2001188986A (en) * | 1999-12-30 | 2001-07-10 | Hiroshi Tanaka | Method for measuring vehicle travel speed and traffic volume on road by aerial photography |
US6697730B2 (en) | 2000-04-04 | 2004-02-24 | Georgia Tech Research Corp. | Communications and computing based urban transit system |
JP4517256B2 (en) | 2000-04-25 | 2010-08-04 | ソニー株式会社 | Car equipment |
US6553301B1 (en) * | 2000-05-19 | 2003-04-22 | General Motors Corporation | System and method of providing optimal fuel economy for automobiles |
US6765495B1 (en) * | 2000-06-07 | 2004-07-20 | Hrl Laboratories, Llc | Inter vehicle communication system |
US8346580B2 (en) * | 2000-06-09 | 2013-01-01 | Flash Seats, Llc | System and method for managing transfer of ownership rights to access to a venue and allowing access to the venue to patron with the ownership right |
US6317686B1 (en) * | 2000-07-21 | 2001-11-13 | Bin Ran | Method of providing travel time |
US7203598B1 (en) * | 2000-09-26 | 2007-04-10 | Nortel Networks Limited | Traffic information and automatic route guidance |
JP2002123894A (en) * | 2000-10-16 | 2002-04-26 | Hitachi Ltd | Method and apparatus for controlling probe car and traffic control system using probe car |
US6895329B1 (en) * | 2000-10-30 | 2005-05-17 | Board Of Trustees Of The University Of Illinois | Method and system for querying in a moving object database |
US6615133B2 (en) * | 2001-02-27 | 2003-09-02 | International Business Machines Corporation | Apparatus, system, method and computer program product for determining an optimum route based on historical information |
CA2339433A1 (en) * | 2001-03-07 | 2002-09-07 | Lawrence Solomon | Road toll system for alleviating traffic congestion |
US6615137B2 (en) * | 2001-06-26 | 2003-09-02 | Medius, Inc. | Method and apparatus for transferring information between vehicles |
US6950504B1 (en) * | 2001-07-06 | 2005-09-27 | Cingular Wireless Ii, Inc. | Method and apparatus for providing personal audio alert messaging for audio alerting capable terminals |
DE60121963T2 (en) | 2001-10-15 | 2007-01-18 | Ford Global Technologies, LLC, Dearborn | Method and device for controlling a vehicle |
JP3933929B2 (en) * | 2001-12-28 | 2007-06-20 | アルパイン株式会社 | Navigation device |
US20030162523A1 (en) * | 2002-02-27 | 2003-08-28 | Michael Kapolka | Vehicle telemetry system and method |
US7221287B2 (en) | 2002-03-05 | 2007-05-22 | Triangle Software Llc | Three-dimensional traffic report |
ES2425555T3 (en) * | 2002-04-30 | 2013-10-16 | Telmap Ltd. | Navigation system that uses corridor maps |
US7483840B2 (en) * | 2002-08-23 | 2009-01-27 | Atera /Solutions Llc | Randomized competitive insurance pricing system and method |
CN100507450C (en) | 2002-09-24 | 2009-07-01 | 三洋电机株式会社 | Navigation apparatus and server apparatus |
JP3885716B2 (en) * | 2002-11-21 | 2007-02-28 | 日産自動車株式会社 | Recommended operation amount generator for vehicles |
US7155339B2 (en) * | 2003-06-13 | 2006-12-26 | Alpine Electronics, Inc. | Display method and apparatus for navigation system for searching POI and arranging listing order of POI |
WO2005003885A2 (en) * | 2003-07-07 | 2005-01-13 | Sensomatix Ltd. | Traffic information system |
DE10343683A1 (en) | 2003-09-20 | 2005-04-21 | Daimler Chrysler Ag | Information system for motor vehicles |
JP4507815B2 (en) * | 2004-07-09 | 2010-07-21 | アイシン・エィ・ダブリュ株式会社 | Signal information creating method, signal guide information providing method, and navigation apparatus |
US7091880B2 (en) * | 2004-07-15 | 2006-08-15 | Raytheon Company | Licensed driver detection for high occupancy toll lane qualification |
US7831384B2 (en) * | 2004-10-29 | 2010-11-09 | Aol Inc. | Determining a route to destination based on partially completed route |
US7835859B2 (en) * | 2004-10-29 | 2010-11-16 | Aol Inc. | Determining a route to a destination based on partially completed route |
US7348895B2 (en) * | 2004-11-03 | 2008-03-25 | Lagassey Paul J | Advanced automobile accident detection, data recordation and reporting system |
US7519564B2 (en) * | 2004-11-16 | 2009-04-14 | Microsoft Corporation | Building and using predictive models of current and future surprises |
US8832121B2 (en) * | 2005-02-02 | 2014-09-09 | Accuweather, Inc. | Location-based data communications system and method |
US7501947B2 (en) | 2005-05-04 | 2009-03-10 | Tc License, Ltd. | RFID tag with small aperture antenna |
BRPI0520270B1 (en) * | 2005-06-01 | 2019-10-01 | Allstate Insurance Company | EVALUATION METHOD OF AT LEAST ONE INDIVIDUAL |
US7720630B1 (en) * | 2005-06-02 | 2010-05-18 | Wsi Corporation | Personalized transportation information system |
JP4369403B2 (en) | 2005-07-05 | 2009-11-18 | 株式会社豊田中央研究所 | Acceleration feeling evaluation apparatus and vehicle control apparatus |
ES2374221T3 (en) * | 2005-07-11 | 2012-02-14 | Volvo Technology Corporation | METHODS AND DEVICE FOR CARRYING OUT THE IDENTITY CHECK OF A DRIVER. |
CA2621150A1 (en) * | 2005-09-02 | 2007-03-08 | Hntb Holdings Ltd | System and method for collecting and transporting simulation data |
TWI287514B (en) * | 2005-11-03 | 2007-10-01 | Ind Tech Res Inst | Inter-vehicle communication and warning apparatus |
GB0523512D0 (en) | 2005-11-18 | 2005-12-28 | Applied Generics Ltd | Enhancing traffic and navigation information with visual and audio data |
KR100797394B1 (en) | 2005-12-08 | 2008-01-28 | 한국전자통신연구원 | Apparatus and Method for Providing Traffic Jam Information for Installing on the Road |
JP4463757B2 (en) * | 2005-12-09 | 2010-05-19 | 株式会社小松製作所 | Vehicle travel control device |
EP1969456A4 (en) * | 2005-12-12 | 2015-11-04 | Tegic Comm Llc | Mobile device retrieval and navigation |
US8942483B2 (en) | 2009-09-14 | 2015-01-27 | Trimble Navigation Limited | Image-based georeferencing |
US7495550B2 (en) * | 2005-12-28 | 2009-02-24 | Palo Alto Research Center Incorporated | Method and apparatus for rear-end collision warning and accident mitigation |
GB2434346B (en) * | 2006-01-18 | 2011-01-05 | Airmax Group Plc | Method and system for driver style monitoring and analysing |
US7912628B2 (en) * | 2006-03-03 | 2011-03-22 | Inrix, Inc. | Determining road traffic conditions using data from multiple data sources |
US20070208493A1 (en) | 2006-03-03 | 2007-09-06 | Inrix, Inc. | Identifying unrepresentative road traffic condition data obtained from mobile data sources |
ATE409307T1 (en) * | 2006-03-31 | 2008-10-15 | Research In Motion Ltd | USER INTERFACE METHOD AND APPARATUS FOR CONTROLLING THE VISUAL DISPLAY OF MAPS WITH SELECTABLE MAP ELEMENTS IN MOBILE COMMUNICATION DEVICES |
US20080228365A1 (en) * | 2006-04-05 | 2008-09-18 | White Steven C | Vehicle power inhibiter |
US9067565B2 (en) * | 2006-05-22 | 2015-06-30 | Inthinc Technology Solutions, Inc. | System and method for evaluating driver behavior |
JP4342535B2 (en) * | 2006-07-10 | 2009-10-14 | トヨタ自動車株式会社 | Congestion degree creation method, congestion degree creation device |
US7908076B2 (en) * | 2006-08-18 | 2011-03-15 | Inrix, Inc. | Representative road traffic flow information based on historical data |
US7822546B2 (en) * | 2006-09-05 | 2010-10-26 | Garmin Switzerland Gmbh | Travel guide and schedule-based routing device and method |
JP4842070B2 (en) * | 2006-09-25 | 2011-12-21 | アルパイン株式会社 | In-vehicle navigation device, search data creation method, and guidance route search method |
JP4130847B2 (en) * | 2006-09-28 | 2008-08-06 | 松下電器産業株式会社 | Destination prediction apparatus and method |
US8531521B2 (en) * | 2006-10-06 | 2013-09-10 | Sightlogix, Inc. | Methods and apparatus related to improved surveillance using a smart camera |
US7603233B2 (en) * | 2006-10-16 | 2009-10-13 | Alpine Electronics, Inc. | Map matching method and apparatus for navigation system |
US8755991B2 (en) | 2007-01-24 | 2014-06-17 | Tomtom Global Assets B.V. | Method and structure for vehicular traffic prediction with link interactions and missing real-time data |
US20080204277A1 (en) | 2007-02-27 | 2008-08-28 | Roy Sumner | Adaptive traffic signal phase change system |
US7783417B2 (en) * | 2007-03-09 | 2010-08-24 | Mitac International Corporation | Methods and apparatus for determining a route having an estimated minimum fuel usage for a vehicle |
US20080262710A1 (en) * | 2007-04-23 | 2008-10-23 | Jing Li | Method and system for a traffic management system based on multiple classes |
US20080300776A1 (en) | 2007-06-01 | 2008-12-04 | Petrisor Gregory C | Traffic lane management system |
JP4793331B2 (en) * | 2007-06-13 | 2011-10-12 | 日産自動車株式会社 | Control device for vehicle shifting |
US20090005964A1 (en) * | 2007-06-28 | 2009-01-01 | Apple Inc. | Intelligent Route Guidance |
US7720844B2 (en) * | 2007-07-03 | 2010-05-18 | Vulcan, Inc. | Method and system for continuous, dynamic, adaptive searching based on a continuously evolving personal region of interest |
US9076331B2 (en) | 2007-07-16 | 2015-07-07 | Crucs Holdings, Llc | System and method to monitor vehicles on a roadway and to control driving restrictions of vehicle drivers |
US10083607B2 (en) * | 2007-09-07 | 2018-09-25 | Green Driver, Inc. | Driver safety enhancement using intelligent traffic signals and GPS |
US7755509B2 (en) * | 2007-09-20 | 2010-07-13 | Traffic.Com, Inc. | Use of pattern matching to predict actual traffic conditions of a roadway segment |
JP4561802B2 (en) * | 2007-10-02 | 2010-10-13 | 株式会社デンソー | Map display device and program |
US8849183B2 (en) * | 2007-10-05 | 2014-09-30 | Qualcomm Incorporated | Location and time based filtering of broadcast information |
FR2929034B1 (en) * | 2008-03-20 | 2010-04-16 | Armines Ass Pour La Rech Et Le | SYSTEM AND METHOD FOR INFORMATION ON TRAFFIC IN A ROAD NETWORK |
US20090265105A1 (en) * | 2008-04-21 | 2009-10-22 | Igt | Real-time navigation devices, systems and methods |
US7519472B1 (en) | 2008-05-15 | 2009-04-14 | International Business Machines Corporation | Inferring static traffic artifact presence, location, and specifics from aggregated navigation system data |
JP4547721B2 (en) * | 2008-05-21 | 2010-09-22 | 株式会社デンソー | Automotive information provision system |
US20090322560A1 (en) * | 2008-06-30 | 2009-12-31 | General Motors Corporation | In-vehicle alert delivery maximizing communications efficiency and subscriber privacy |
JP4733165B2 (en) * | 2008-06-30 | 2011-07-27 | 株式会社デンソー | Vehicle navigation system |
US20100023265A1 (en) * | 2008-07-24 | 2010-01-28 | Gm Global Technology Operations, Inc. | Adaptive vehicle control system with integrated driving style recognition |
KR101028328B1 (en) * | 2008-08-26 | 2011-04-12 | 현대자동차주식회사 | System for evaluating point of interest and method thereof |
US20100057358A1 (en) | 2008-08-28 | 2010-03-04 | TeleType Co., Inc. | Portable gps map device for commercial vehicle industry |
TWI382156B (en) | 2008-09-17 | 2013-01-11 | Inventec Appliances Corp | Portable navigation device and method |
US8009062B2 (en) * | 2008-09-22 | 2011-08-30 | Rothschild Leigh M | Vehicle traffic flow data acquisition and distribution |
US8010285B1 (en) * | 2008-09-30 | 2011-08-30 | Denise Jason A | Electronic navigation related technology |
US8150611B2 (en) * | 2008-09-30 | 2012-04-03 | International Business Machines Corporation | System and methods for providing predictive traffic information |
US20100094543A1 (en) * | 2008-10-09 | 2010-04-15 | 411 Web Directory | Systems And Methods For Providing Geography-Based Tours |
US8775070B1 (en) * | 2008-10-15 | 2014-07-08 | Intuit Inc. | Method and system for user preference-based route calculation |
EP2342536A1 (en) * | 2008-11-06 | 2011-07-13 | TomTom International B.V. | Data acquisition apparatus, data acquisition system and method of acquiring data |
US8156068B2 (en) * | 2008-11-13 | 2012-04-10 | Telecommunication Systems, Inc. | Predictive ephemeral points-of-interest (PEPOI) |
CA2749685A1 (en) * | 2008-11-13 | 2010-05-20 | Aser Rich Limited | System and method for improved vehicle safety through enhanced situation awareness of a driver of a vehicle |
US8351912B2 (en) * | 2008-12-12 | 2013-01-08 | Research In Motion Limited | System and method for providing traffic notifications to mobile devices |
US20100153191A1 (en) * | 2008-12-17 | 2010-06-17 | International Business Machines Corporation | Variable toll fee selection from geographic indicia |
US20100157061A1 (en) * | 2008-12-24 | 2010-06-24 | Igor Katsman | Device and method for handheld device based vehicle monitoring and driver assistance |
US8600577B2 (en) * | 2008-12-29 | 2013-12-03 | Motorola Mobility Llc | Navigation system and methods for generating enhanced search results |
DE112009004307B4 (en) | 2009-01-19 | 2017-03-23 | Toyota Jidosha Kabushiki Kaisha | Vehicle control device |
US8458177B2 (en) * | 2009-02-02 | 2013-06-04 | Yahoo! Inc. | Automated search |
US8188887B2 (en) * | 2009-02-13 | 2012-05-29 | Inthinc Technology Solutions, Inc. | System and method for alerting drivers to road conditions |
JP5152677B2 (en) * | 2009-02-26 | 2013-02-27 | アイシン・エィ・ダブリュ株式会社 | Navigation device and navigation program |
US8457888B2 (en) * | 2009-03-08 | 2013-06-04 | Mitac International Corp. | Method for reminding users about future appointments while taking into account traveling time to the appointment location |
US8838370B2 (en) * | 2009-03-09 | 2014-09-16 | Empire Technology Development Llc | Traffic flow model to provide traffic flow information |
US8965670B2 (en) * | 2009-03-27 | 2015-02-24 | Hti Ip, L.L.C. | Method and system for automatically selecting and displaying traffic images |
CA2756183A1 (en) * | 2009-03-30 | 2010-10-07 | Aha Mobile, Inc. | Predictive search with location-based application |
US9154982B2 (en) * | 2009-04-02 | 2015-10-06 | Trafficcast International, Inc. | Method and system for a traffic management network |
WO2010114619A1 (en) * | 2009-04-03 | 2010-10-07 | Certusview Technologies, Llc | Methods, apparatus, and systems for acquiring and analyzing vehicle data and generating an electronic representation of vehicle operations |
US20100262449A1 (en) * | 2009-04-09 | 2010-10-14 | Access Mobility, Inc. | Context based mobile marketing |
US9141087B2 (en) | 2009-04-26 | 2015-09-22 | Nike, Inc. | Athletic watch |
WO2010132677A1 (en) * | 2009-05-13 | 2010-11-18 | Rutgers, The State University | Vehicular information systems and methods |
US20100283432A1 (en) * | 2009-05-11 | 2010-11-11 | Simon Ellwanger | Vehicle Timing Apparatus |
US8325642B1 (en) * | 2009-05-14 | 2012-12-04 | Cellco Partnership | Redirection of message from mobile station based on identity of mobile station |
US8977489B2 (en) * | 2009-05-18 | 2015-03-10 | GM Global Technology Operations LLC | Turn by turn graphical navigation on full windshield head-up display |
US9767209B2 (en) * | 2009-05-28 | 2017-09-19 | Apple Inc. | Search filtering based on expected future time and location |
US8577543B2 (en) * | 2009-05-28 | 2013-11-05 | Intelligent Mechatronic Systems Inc. | Communication system with personal information management and remote vehicle monitoring and control features |
US9086292B2 (en) * | 2009-06-26 | 2015-07-21 | Microsoft Technology Licensing, Llc | Routing, alerting, and transportation guidance based on preferences and learned or inferred risks and desirabilities |
US9552726B2 (en) * | 2009-08-24 | 2017-01-24 | Here Global B.V. | Providing driving condition alerts using road attribute data |
US9183740B2 (en) * | 2009-09-24 | 2015-11-10 | Mitsubishi Electric Corporation | Travel pattern generation device |
US8433512B1 (en) * | 2009-11-12 | 2013-04-30 | Google Inc. | Enhanced identification of interesting points-of-interest |
JP4992959B2 (en) | 2009-11-30 | 2012-08-08 | 株式会社デンソー | Collision avoidance support device and collision avoidance support program |
EP2330562B1 (en) * | 2009-12-02 | 2019-03-13 | Telit Automotive Solutions NV | Smart road-toll-system |
US8396663B2 (en) * | 2009-12-15 | 2013-03-12 | Navteq B.V. | Speed profile dictionary |
US8510045B2 (en) * | 2009-12-22 | 2013-08-13 | Steven L. Rueben | Digital maps displaying search-resulting points-of-interest in user delimited regions |
EP2343694B1 (en) * | 2009-12-29 | 2012-03-14 | Research In Motion Limited | System and method of sending an arrival time estimate |
EP2341493A1 (en) * | 2009-12-29 | 2011-07-06 | Research In Motion Limited | System and method for faster detection of traffic jams |
US9518833B2 (en) * | 2009-12-29 | 2016-12-13 | Blackberry Limited | System and method of automatic destination selection |
US8532920B2 (en) * | 2010-01-22 | 2013-09-10 | Blackberry Limited | Automatic origin determination for faster route request initiation and resulting system response time |
DE102011003993A1 (en) * | 2010-02-15 | 2011-08-18 | DENSO CORPORATION, Aichi-pref. | Charge controller and navigation device for a plug-in vehicle |
CA2789699C (en) * | 2010-03-11 | 2016-05-03 | Inrix, Inc. | Learning road navigation paths based on aggregate driver behavior |
DE102010011497A1 (en) * | 2010-03-16 | 2011-09-22 | GM Global Technology Operations LLC , (n. d. Ges. d. Staates Delaware) | Method for avoiding or mitigating a collision, control device for a driver assistance system and vehicle |
DE102010014076A1 (en) * | 2010-04-07 | 2011-10-13 | Gm Global Technology Operations Llc (N.D.Ges.D. Staates Delaware) | Method for adapting a driving behavior of a vehicle when changing drivers |
US20110301835A1 (en) * | 2010-06-07 | 2011-12-08 | James Bongiorno | Portable vacation/travel planner, and family tour guide device |
US8645061B2 (en) * | 2010-06-16 | 2014-02-04 | Microsoft Corporation | Probabilistic map matching from a plurality of observational and contextual factors |
US9047778B1 (en) * | 2010-06-25 | 2015-06-02 | Cellco Partnership | Collision avoidance system using telematics unit |
EP2609582B1 (en) * | 2010-08-23 | 2019-10-09 | Status Technologies Pty Ltd | A vehicle safety warning and information system |
US20120065834A1 (en) * | 2010-09-10 | 2012-03-15 | Accenture Global Services Limited | Driving management system and method |
US8738283B2 (en) * | 2010-09-24 | 2014-05-27 | Telenav, Inc. | Navigation system with parking lot integrated routing mechanism and method of operation thereof |
DE102010041544B4 (en) * | 2010-09-28 | 2023-05-04 | Bayerische Motoren Werke Aktiengesellschaft | Driver assistance system to support the driver in consumption-controlled driving |
US8509982B2 (en) * | 2010-10-05 | 2013-08-13 | Google Inc. | Zone driving |
US8238872B2 (en) * | 2010-10-18 | 2012-08-07 | GM Global Technology Operations LLC | Vehicle data management system and method |
US20120109521A1 (en) * | 2010-10-27 | 2012-05-03 | Reagan Inventions, Llc | System and method of integrating lane position monitoring with locational information systems |
US8552886B2 (en) * | 2010-11-24 | 2013-10-08 | Bcs Business Consulting Services Pte Ltd. | Crash warning system for motor vehicles |
EP2469231A1 (en) * | 2010-12-22 | 2012-06-27 | Sony Ericsson Mobile Communications AB | Method and arrangement relating to navigation |
CN102073846B (en) * | 2010-12-15 | 2013-06-05 | 同济大学 | Method for acquiring traffic information based on aerial images |
US9134137B2 (en) * | 2010-12-17 | 2015-09-15 | Microsoft Technology Licensing, Llc | Mobile search based on predicted location |
US20130282264A1 (en) * | 2010-12-31 | 2013-10-24 | Edwin Bastiaensen | Systems and methods for obtaining and using traffic flow information |
WO2012089282A1 (en) * | 2010-12-31 | 2012-07-05 | Tomtom Belgium Nv | Navigation methods and systems |
DE102011000409A1 (en) * | 2011-01-31 | 2012-08-02 | Dr. Ing. H.C. F. Porsche Aktiengesellschaft | Method for evaluating driving dynamic characteristic of driving profile adapted to motor vehicle, involves performing road test with test persons, which performs road test with given driving style |
US20120215594A1 (en) * | 2011-02-18 | 2012-08-23 | Amtech Systems, LLC | System and method for gps lane and toll determination and asset position matching |
US8660864B2 (en) * | 2011-02-28 | 2014-02-25 | Hartford Fire Insurance Company | Systems and methods for intelligent underwriting based on community or social network data |
US9221428B2 (en) * | 2011-03-02 | 2015-12-29 | Automatic Labs Inc. | Driver identification system and methods |
JP2012226392A (en) | 2011-04-14 | 2012-11-15 | Honda Elesys Co Ltd | Drive support system |
US9229905B1 (en) * | 2011-04-22 | 2016-01-05 | Angel A. Penilla | Methods and systems for defining vehicle user profiles and managing user profiles via cloud systems and applying learned settings to user profiles |
WO2012146475A2 (en) | 2011-04-27 | 2012-11-01 | Robert Bosch Gmbh | Vehicle navigation system - maximum toll limit |
JP5763757B2 (en) | 2011-05-20 | 2015-08-12 | 本田技研工業株式会社 | Lane change support system |
US8521407B2 (en) * | 2011-06-10 | 2013-08-27 | GM Global Technology Operations LLC | System and method for ensuring a person reaches a destination on time |
US8788113B2 (en) * | 2011-06-13 | 2014-07-22 | Ford Global Technologies, Llc | Vehicle driver advisory system and method |
US20110307188A1 (en) * | 2011-06-29 | 2011-12-15 | State Farm Insurance | Systems and methods for providing driver feedback using a handheld mobile device |
US8996304B2 (en) * | 2011-06-29 | 2015-03-31 | Intel Corporation | Customized travel route system |
US8949212B1 (en) * | 2011-07-08 | 2015-02-03 | Hariharan Dhandapani | Location-based informaton display |
US8740165B2 (en) * | 2011-07-22 | 2014-06-03 | Larry O'Kasick | Point-of-sale organizer |
US20130024309A1 (en) | 2011-07-24 | 2013-01-24 | Tuomas Sandholm | Barter chains |
WO2013016719A1 (en) * | 2011-07-28 | 2013-01-31 | School Improvement Network, Llc | Management and provision of interactive content |
US20140172521A1 (en) * | 2011-07-29 | 2014-06-19 | Nec Corporation | Traffic Control System, Congestion Control Method, Information Processing Apparatus, and Control Method and Storage Medium Therefor |
JP5741310B2 (en) * | 2011-08-10 | 2015-07-01 | 富士通株式会社 | Train length measuring device, train length measuring method, and train length measuring computer program |
US9361271B2 (en) * | 2011-09-27 | 2016-06-07 | Wipro Limited | Systems and methods to enable eco-driving |
US8874367B2 (en) * | 2011-10-14 | 2014-10-28 | Equilateral Technologies, Inc. | Method for estimating and displaying range of a vehicle |
US20130110633A1 (en) * | 2011-11-02 | 2013-05-02 | Digital Footsteps, Ltd. | Adaptive presentation of guided tour information on mobile client terminal(s) |
US20130132434A1 (en) * | 2011-11-22 | 2013-05-23 | Inrix, Inc. | User-assisted identification of location conditions |
JP5724864B2 (en) * | 2011-12-13 | 2015-05-27 | アイシン・エィ・ダブリュ株式会社 | Display system, display method, and display program |
US8892355B2 (en) * | 2011-12-21 | 2014-11-18 | Telenav, Inc. | Navigation system with point of interest validation mechanism and method of operation thereof |
US20120109508A1 (en) | 2011-12-28 | 2012-05-03 | Ariel Inventions, Llc | Method and system for route navigation based on energy efficiency |
US8855925B2 (en) * | 2012-01-20 | 2014-10-07 | GM Global Technology Operations LLC | Adaptable navigation device |
US8750618B2 (en) * | 2012-01-31 | 2014-06-10 | Taif University | Method for coding images with shape and detail information |
US8635018B2 (en) * | 2012-02-03 | 2014-01-21 | International Business Machines Corporation | Managing a driver profile |
US9381916B1 (en) * | 2012-02-06 | 2016-07-05 | Google Inc. | System and method for predicting behaviors of detected objects through environment representation |
JP5704086B2 (en) * | 2012-02-07 | 2015-04-22 | 株式会社デンソー | Car navigation system |
US20130218604A1 (en) * | 2012-02-21 | 2013-08-22 | Elwha Llc | Systems and methods for insurance based upon monitored characteristics of a collision detection system |
US20130219307A1 (en) * | 2012-02-21 | 2013-08-22 | Artisan Mobile, Inc. | System and method for runtime user interface management |
JP2013171491A (en) * | 2012-02-22 | 2013-09-02 | Nippon Expressway Research Institute Co Ltd | Traffic estimation system using single image |
US8843158B2 (en) * | 2012-02-22 | 2014-09-23 | Apple Inc. | Delivering content by predicting predetermined routes using wireless networks |
US10311651B2 (en) * | 2012-02-29 | 2019-06-04 | Conduent Business Services, Llc | Method and system for providing dynamic pricing algorithm with embedded controller for high occupancy toll lanes |
US9200918B2 (en) * | 2012-03-09 | 2015-12-01 | Apple Inc. | Intelligent destination recommendations based on historical data |
US8788121B2 (en) | 2012-03-09 | 2014-07-22 | Proxy Technologies, Inc. | Autonomous vehicle and method for coordinating the paths of multiple autonomous vehicles |
US9147298B2 (en) * | 2012-03-14 | 2015-09-29 | Flextronics Ap, Llc | Behavior modification via altered map routes based on user profile information |
US20130278441A1 (en) * | 2012-04-24 | 2013-10-24 | Zetta Research and Development, LLC - ForC Series | Vehicle proxying |
KR101860540B1 (en) * | 2012-04-26 | 2018-05-23 | 한국전자통신연구원 | Portable terminal and method for sharing location information between users |
DE102012207859A1 (en) * | 2012-05-11 | 2013-11-14 | Robert Bosch Gmbh | Method for creating a driving profile |
JPWO2013171898A1 (en) * | 2012-05-18 | 2016-01-07 | トヨタ自動車株式会社 | Vehicle information display device |
US8799032B2 (en) * | 2012-05-22 | 2014-08-05 | Hartford Fire Insurance Company | System and method to predict an insurance policy benefit associated with telematics data |
US8972318B2 (en) | 2012-05-31 | 2015-03-03 | Qualcomm Incorporated | Predicting user behavior using feedback on previously run predictive searches |
US9430941B2 (en) * | 2012-06-10 | 2016-08-30 | Apple Inc. | Harvesting traffic information from mobile devices |
US20130338914A1 (en) * | 2012-06-14 | 2013-12-19 | Wavemarket Inc. | System and method for notifying vehicle driver of localized driving conditions |
US9053632B2 (en) * | 2012-06-29 | 2015-06-09 | International Business Machines Corporation | Real-time traffic prediction and/or estimation using GPS data with low sampling rates |
CN102855759B (en) * | 2012-07-05 | 2014-04-09 | 中国科学院遥感应用研究所 | Automatic collecting method of high-resolution satellite remote sensing traffic flow information |
JP6215950B2 (en) * | 2012-09-17 | 2017-10-18 | ボルボ ラストバグナー アクチエボラグ | How to give a vehicle driver an instructional message based on the situation |
US9110196B2 (en) * | 2012-09-20 | 2015-08-18 | Google, Inc. | Detecting road weather conditions |
US20140085106A1 (en) * | 2012-09-21 | 2014-03-27 | Checkers Industrial Products, Llc | Vehicle proximity warning system and methods |
SE537958C2 (en) * | 2012-09-24 | 2015-12-08 | Scania Cv Ab | Procedure, measuring device and control unit for adapting vehicle train control |
US9037519B2 (en) | 2012-10-18 | 2015-05-19 | Enjoyor Company Limited | Urban traffic state detection based on support vector machine and multilayer perceptron |
CN202944628U (en) * | 2012-10-19 | 2013-05-22 | 王克远 | Double zipper transparent storage box |
DE102012219927A1 (en) * | 2012-10-31 | 2014-04-30 | Bayerische Motoren Werke Aktiengesellschaft | Vehicle assistance device |
US9208684B2 (en) * | 2012-11-01 | 2015-12-08 | Verizon Patent And Licensing Inc. | Travel optimization system |
US9950708B1 (en) * | 2012-11-02 | 2018-04-24 | Waymo Llc | Adaptation of autonomous driving behaviour based on occupant presence and position |
US10088316B2 (en) * | 2012-11-28 | 2018-10-02 | Toyota Motor Engineering & Manufacturing North America, Inc. | Navigation systems and vehicles for predicting routes |
US20140172294A1 (en) * | 2012-12-14 | 2014-06-19 | Magnasoft Consulting India Pvt. Ltd | Method and system for predicting expected time of arrival of objects |
US8892359B2 (en) * | 2013-01-11 | 2014-11-18 | Toyota Motor Engineering & Manufacturing North America, Inc. | Systems and methods for estimating time of arrival for vehicle navigation |
US9439036B2 (en) * | 2013-01-25 | 2016-09-06 | Visa International Service Association | Systems and methods to select locations of interest based on distance from route points or route paths |
WO2014160027A1 (en) * | 2013-03-13 | 2014-10-02 | Image Sensing Systems, Inc. | Roadway sensing systems |
US9082014B2 (en) * | 2013-03-14 | 2015-07-14 | The Nielsen Company (Us), Llc | Methods and apparatus to estimate demography based on aerial images |
US9200915B2 (en) * | 2013-06-08 | 2015-12-01 | Apple Inc. | Mapping application with several user interfaces |
CN105229422B (en) * | 2013-03-15 | 2018-04-27 | 大众汽车有限公司 | Automatic Pilot route planning application |
US9751534B2 (en) * | 2013-03-15 | 2017-09-05 | Honda Motor Co., Ltd. | System and method for responding to driver state |
US9631930B2 (en) * | 2013-03-15 | 2017-04-25 | Apple Inc. | Warning for frequently traveled trips based on traffic |
US20140316958A1 (en) * | 2013-04-17 | 2014-10-23 | Green Edge Technologies, Inc. | Systems, devices, and methods for energy account management |
US9454905B2 (en) * | 2013-04-29 | 2016-09-27 | Global Foundries Inc. | Safe distance determination |
DE102013210941A1 (en) * | 2013-06-12 | 2014-12-18 | Robert Bosch Gmbh | Method and device for operating a vehicle |
US20150014901A1 (en) * | 2013-07-09 | 2015-01-15 | NOVA LEATHER ENTERPRISES Co. LTD. | Method for manufacturing non-sewing three-dimensional fabric capable of polychrome printing |
US9111453B1 (en) * | 2013-08-01 | 2015-08-18 | Mohammad A. Alselimi | Traffic management server and a traffic recording apparatus |
US9211891B2 (en) * | 2013-08-02 | 2015-12-15 | Inrix Inc. | Personalized vehicle driving suggestions |
US9175970B2 (en) * | 2013-08-02 | 2015-11-03 | Cummins Inc. | Online optimal refueling management |
US9243925B2 (en) * | 2013-08-27 | 2016-01-26 | Google Inc. | Generating a sequence of lane-specific driving directions |
US9232119B2 (en) * | 2013-10-08 | 2016-01-05 | Raytheon Company | Integrating image frames |
WO2015052953A1 (en) * | 2013-10-08 | 2015-04-16 | 日本電気株式会社 | Vehicle guidance system, vehicle guidance method, management device, and control method for same |
US9361690B2 (en) * | 2013-10-09 | 2016-06-07 | Xerox Corporation | Video based method and system for automated side-by-side traffic load balancing |
US9435660B2 (en) * | 2013-10-16 | 2016-09-06 | Mapquest, Inc. | Systems and methods for initiating mapping exit routines and rating highway exits |
US20150120192A1 (en) * | 2013-10-25 | 2015-04-30 | Aviv Ron | Navigation guidance including provision of stops |
US9183743B2 (en) * | 2013-10-31 | 2015-11-10 | Bayerische Motoren Werke Aktiengesellschaft | Systems and methods for estimating traffic signal information |
US9485543B2 (en) * | 2013-11-12 | 2016-11-01 | Google Inc. | Methods, systems, and media for presenting suggestions of media content |
US9517771B2 (en) * | 2013-11-22 | 2016-12-13 | Ford Global Technologies, Llc | Autonomous vehicle modes |
JP6230620B2 (en) * | 2013-12-10 | 2017-11-15 | 三菱電機株式会社 | Travel control device |
KR20150068218A (en) * | 2013-12-11 | 2015-06-19 | 경북대학교 산학협력단 | Vehicular Navigation System |
WO2015088522A1 (en) * | 2013-12-11 | 2015-06-18 | Intel Corporation | Individual driving preference adapted computerized assist or autonomous driving of vehicles |
US9251630B2 (en) * | 2013-12-17 | 2016-02-02 | At&T Intellectual Property I, L.P. | Method, computer-readable storage device and apparatus for exchanging vehicle information |
US20150199664A1 (en) * | 2014-01-15 | 2015-07-16 | Mastercard International Incorporated | Methods, systems, and computer readable media for facilitating access to transportation services |
US9230435B2 (en) * | 2014-01-28 | 2016-01-05 | Hti Ip, Llc | Driver controllable traffic signal |
US20150228129A1 (en) * | 2014-02-10 | 2015-08-13 | Metromile, Inc. | System and method for profiling vehicle usage |
JP6298322B2 (en) * | 2014-02-27 | 2018-03-20 | 株式会社ゼンリン | Route search device, route search method and program |
US9539999B2 (en) * | 2014-02-28 | 2017-01-10 | Ford Global Technologies, Llc | Vehicle operator monitoring and operations adjustments |
US10692370B2 (en) * | 2014-03-03 | 2020-06-23 | Inrix, Inc. | Traffic obstruction detection |
US9605606B2 (en) * | 2014-03-31 | 2017-03-28 | Toyota Motor Engineering & Manufacturing North America, Inc. | System and method for improving energy efficiency of a vehicle based on determined relationships between a plurality of routes |
US9390621B2 (en) * | 2014-06-04 | 2016-07-12 | Cuende Infometrics, S.A. | System and method for measuring the real traffic flow of an area |
US9779623B2 (en) * | 2014-07-02 | 2017-10-03 | Lenovo Enterprise Solutions (Singapore) Pte. Ltd. | Communication of alerts to vehicles based on vehicle movement |
JP2016033501A (en) * | 2014-07-31 | 2016-03-10 | トヨタ自動車株式会社 | Vehicle information provision device |
US20160061617A1 (en) * | 2014-09-02 | 2016-03-03 | Microsoft Corporation | Providing in-navigation search results that reduce route disruption |
US10140785B1 (en) * | 2014-09-02 | 2018-11-27 | Metromile, Inc. | Systems and methods for determining fuel information of a vehicle |
US9997077B2 (en) * | 2014-09-04 | 2018-06-12 | Honda Motor Co., Ltd. | Vehicle operation assistance |
KR20170041162A (en) * | 2014-09-05 | 2017-04-14 | 요코하마 고무 가부시키가이샤 | Collision avoidance system and collision avoidance method |
US20160123752A1 (en) * | 2014-10-30 | 2016-05-05 | Microsoft Corporation | Estimating and predicting fuel usage with smartphone |
DE102015105581A1 (en) * | 2014-11-03 | 2016-05-04 | Audi Ag | System and method for monitoring the health and / or health of a vehicle occupant |
US20160147416A1 (en) * | 2014-11-21 | 2016-05-26 | Here Global B.V. | Method and apparatus for determining a representation of a point of interest based on user experience |
WO2016086139A1 (en) * | 2014-11-26 | 2016-06-02 | Ispd, Inc. | System and method for traffic decongestion |
US10175054B2 (en) * | 2015-01-11 | 2019-01-08 | Microsoft Technology Licensing, Llc | Predicting and utilizing variability of travel times in mapping services |
US9435657B2 (en) * | 2015-01-14 | 2016-09-06 | Telenav, Inc. | Navigation system with an itinerary planning mechanism and method of operation thereof |
US20160209219A1 (en) * | 2015-01-15 | 2016-07-21 | Applied Telemetrics Holdings Inc. | Method of autonomous lane identification for a multilane vehicle roadway |
US9841767B1 (en) * | 2015-01-20 | 2017-12-12 | State Farm Mutual Automobile Insurance Company | Using emergency response system (EMS) vehicle telematics data to reduce accident risk |
US9537971B2 (en) * | 2015-01-29 | 2017-01-03 | Huawei Technologies Co., Ltd. | Systems, devices and methods for distributed content pre-fetching in mobile communication networks |
US10083494B2 (en) * | 2015-01-30 | 2018-09-25 | Huawei Technologies Co., Ltd. | Systems, devices and methods for distributed content pre-fetching to a user device |
US9672759B2 (en) * | 2015-05-11 | 2017-06-06 | Here Global B.V. | Probe based identification and validation of roundabout junctions |
US10097973B2 (en) * | 2015-05-27 | 2018-10-09 | Apple Inc. | Systems and methods for proactively identifying and surfacing relevant content on a touch-sensitive device |
US9638542B2 (en) * | 2015-05-28 | 2017-05-02 | Alpine Electronics, Inc. | Method and system of route scheduling and presenting route-based fuel information |
US9959339B2 (en) * | 2015-07-13 | 2018-05-01 | International Business Machines Corporation | Journey time estimation |
US9803992B2 (en) * | 2015-10-09 | 2017-10-31 | At&T Mobility Ii Llc | Suspending voice guidance during route navigation |
US9908468B2 (en) * | 2016-01-12 | 2018-03-06 | Toyota Motor Engineering & Manufacturing North America, Inc. | Apparatus and method for providing an extended forward collision warning |
US10525848B2 (en) * | 2016-08-02 | 2020-01-07 | Here Global B.V. | Vehicle charging lanes |
US10332039B2 (en) * | 2016-08-17 | 2019-06-25 | International Business Machines Corporation | Intelligent travel planning |
US9921070B1 (en) * | 2016-09-22 | 2018-03-20 | Trimble Inc. | System for planning trips with estimated time of arrival (ETA) and projected time of availability (PTA) calculated for each stop |
US10958742B2 (en) * | 2017-02-16 | 2021-03-23 | International Business Machines Corporation | Cognitive content filtering |
JP6763317B2 (en) * | 2017-02-22 | 2020-09-30 | トヨタ自動車株式会社 | Fuel cell vehicle and its control method |
-
2015
- 2015-02-27 US US15/122,750 patent/US10692370B2/en active Active
- 2015-02-27 WO PCT/US2015/017941 patent/WO2015134311A1/en active Application Filing
- 2015-02-27 EP EP15758511.8A patent/EP3114574A4/en not_active Withdrawn
- 2015-03-01 WO PCT/US2015/018215 patent/WO2015134339A1/en active Application Filing
- 2015-03-01 EP EP15758007.7A patent/EP3113999A4/en not_active Withdrawn
- 2015-03-01 US US15/121,170 patent/US20170032673A1/en not_active Abandoned
- 2015-03-02 WO PCT/US2015/018278 patent/WO2015134372A1/en active Application Filing
- 2015-03-02 EP EP15758684.3A patent/EP3114000A4/en not_active Ceased
- 2015-03-02 WO PCT/US2015/018364 patent/WO2015134410A1/en active Application Filing
- 2015-03-02 WO PCT/US2015/018285 patent/WO2015134376A1/en active Application Filing
- 2015-03-02 EP EP15757727.1A patent/EP3114666A4/en not_active Withdrawn
- 2015-03-02 EP EP15758337.8A patent/EP3114667A4/en not_active Withdrawn
- 2015-03-02 WO PCT/US2015/018310 patent/WO2015134386A2/en active Application Filing
- 2015-03-02 US US15/122,720 patent/US10062280B2/en active Active
- 2015-03-02 EP EP15759006.8A patent/EP3113998A4/en not_active Withdrawn
- 2015-03-02 US US15/122,677 patent/US10629075B2/en active Active
- 2015-03-02 US US15/122,704 patent/US10417910B2/en active Active
- 2015-03-02 US US15/122,734 patent/US20170070616A1/en not_active Abandoned
- 2015-03-03 WO PCT/US2015/018400 patent/WO2015134434A1/en active Application Filing
- 2015-03-03 EP EP15758334.5A patent/EP3114664A4/en not_active Withdrawn
- 2015-03-03 US US15/122,949 patent/US10529231B2/en active Active
- 2015-03-03 US US15/123,022 patent/US10354527B2/en active Active
- 2015-03-03 WO PCT/US2015/018394 patent/WO2015134428A1/en active Application Filing
- 2015-03-03 US US15/123,244 patent/US9685078B2/en active Active
- 2015-03-03 WO PCT/US2015/018383 patent/WO2015134421A1/en active Application Filing
- 2015-03-03 EP EP15757890.7A patent/EP3114575A4/en not_active Withdrawn
- 2015-03-03 EP EP15757848.5A patent/EP3114662A4/en not_active Withdrawn
- 2015-03-03 EP EP15759116.5A patent/EP3114434A4/en not_active Ceased
- 2015-03-03 WO PCT/US2015/018391 patent/WO2015134425A1/en active Application Filing
- 2015-03-03 EP EP15758631.4A patent/EP3114668B1/en active Active
- 2015-03-03 EP EP15758410.3A patent/EP3114663A4/en not_active Withdrawn
- 2015-03-03 EP EP15757978.0A patent/EP3114559A4/en not_active Ceased
- 2015-03-03 WO PCT/US2015/018379 patent/WO2015134417A1/en active Application Filing
- 2015-03-03 US US15/122,986 patent/US20170076598A1/en not_active Abandoned
- 2015-03-03 US US15/121,123 patent/US11292476B2/en active Active
- 2015-03-03 US US15/123,005 patent/US20170084175A1/en not_active Abandoned
- 2015-03-03 EP EP22163536.0A patent/EP4101716B1/en active Active
- 2015-03-03 EP EP15758846.8A patent/EP3114669A4/en not_active Ceased
- 2015-03-03 EP EP15757689.3A patent/EP3114632A4/en not_active Withdrawn
- 2015-03-03 US US15/122,963 patent/US20170076509A1/en not_active Abandoned
- 2015-03-03 EP EP15758305.5A patent/EP3114665A4/en not_active Withdrawn
- 2015-03-03 WO PCT/US2015/018431 patent/WO2015134453A1/en active Application Filing
- 2015-03-03 US US15/123,043 patent/US9940836B2/en active Active
- 2015-03-03 WO PCT/US2015/018458 patent/WO2015134476A1/en active Application Filing
- 2015-03-03 WO PCT/US2015/018544 patent/WO2015134542A1/en active Application Filing
- 2015-03-03 US US15/122,973 patent/US20170076395A1/en not_active Abandoned
- 2015-03-03 WO PCT/US2015/018417 patent/WO2015134444A1/en active Application Filing
- 2015-03-03 US US15/123,241 patent/US20170069201A1/en not_active Abandoned
- 2015-03-03 WO PCT/US2015/018440 patent/WO2015134462A1/en active Application Filing
-
2017
- 2017-06-19 US US15/626,449 patent/US10319232B2/en active Active
-
2019
- 2019-07-12 US US16/509,571 patent/US10803747B2/en active Active
- 2019-09-16 US US16/571,422 patent/US20200013284A1/en active Pending
-
2020
- 2020-01-06 US US16/735,622 patent/US20200143677A1/en not_active Abandoned
- 2020-04-20 US US16/853,215 patent/US11634143B2/en active Active
- 2020-06-22 US US16/907,472 patent/US20200317200A1/en not_active Abandoned
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070050130A1 (en) * | 2005-08-26 | 2007-03-01 | Grimm Donald K | Speed limit advisor |
US20130131969A1 (en) * | 2005-09-22 | 2013-05-23 | Clayco Research Limited Liability Company | Device, system and method for controlling speed of a vehicle using a positional information device |
US20090287401A1 (en) * | 2008-05-19 | 2009-11-19 | Uri Levine | System and method for realtime community information exchange |
US20100007523A1 (en) * | 2008-07-08 | 2010-01-14 | Nuriel Hatav | Driver alert system |
US20120229301A1 (en) * | 2008-07-24 | 2012-09-13 | Cecil Wayne Hilton Goodwin | Driver initiated vehicle-to-vehicle anonymous warning device |
US20100060480A1 (en) * | 2008-09-05 | 2010-03-11 | Gm Global Technology Operations, Inc. | Reliable Packet Delivery Protocol for Geocast Protocol in Disconnected Vehicular Ad Hoc Network |
US20100161195A1 (en) * | 2008-12-18 | 2010-06-24 | Gm Global Technology Operations, Inc. | Method and Apparatus for Speed-Limit Following Cruise Control |
US20110087433A1 (en) * | 2009-10-08 | 2011-04-14 | Honda Motor Co., Ltd. | Method of Dynamic Intersection Mapping |
US8412413B1 (en) * | 2011-12-21 | 2013-04-02 | Delphi Technologies, Inc. | Vehicle windshield display with obstruction detection |
US20140039784A1 (en) * | 2012-07-31 | 2014-02-06 | Flatiron Apps LLC | System and method for hailing taxicabs |
Cited By (192)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10719886B1 (en) | 2014-05-20 | 2020-07-21 | State Farm Mutual Automobile Insurance Company | Accident fault determination for autonomous vehicles |
US10043323B1 (en) * | 2014-05-20 | 2018-08-07 | State Farm Mutual Automotive Insurance Company | Accident response using autonomous vehicle monitoring |
US11288751B1 (en) | 2014-05-20 | 2022-03-29 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US10504306B1 (en) * | 2014-05-20 | 2019-12-10 | State Farm Mutual Automobile Insurance Company | Accident response using autonomous vehicle monitoring |
US11580604B1 (en) | 2014-05-20 | 2023-02-14 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US10748218B2 (en) | 2014-05-20 | 2020-08-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle technology effectiveness determination for insurance pricing |
US10726498B1 (en) | 2014-05-20 | 2020-07-28 | State Farm Mutual Automobile Insurance Company | Accident fault determination for autonomous vehicles |
US10726499B1 (en) | 2014-05-20 | 2020-07-28 | State Farm Mutual Automoible Insurance Company | Accident fault determination for autonomous vehicles |
US11080794B2 (en) | 2014-05-20 | 2021-08-03 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle technology effectiveness determination for insurance pricing |
US11710188B2 (en) | 2014-05-20 | 2023-07-25 | State Farm Mutual Automobile Insurance Company | Autonomous communication feature use and insurance pricing |
US11669090B2 (en) | 2014-05-20 | 2023-06-06 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US11282143B1 (en) | 2014-05-20 | 2022-03-22 | State Farm Mutual Automobile Insurance Company | Fully autonomous vehicle insurance pricing |
US10510123B1 (en) | 2014-05-20 | 2019-12-17 | State Farm Mutual Automobile Insurance Company | Accident risk model determination using autonomous vehicle operating data |
US10529027B1 (en) | 2014-05-20 | 2020-01-07 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US11869092B2 (en) | 2014-05-20 | 2024-01-09 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US11127083B1 (en) | 2014-05-20 | 2021-09-21 | State Farm Mutual Automobile Insurance Company | Driver feedback alerts based upon monitoring use of autonomous vehicle operation features |
US10719885B1 (en) | 2014-05-20 | 2020-07-21 | State Farm Mutual Automobile Insurance Company | Autonomous feature use monitoring and insurance pricing |
US10685403B1 (en) | 2014-05-20 | 2020-06-16 | State Farm Mutual Automobile Insurance Company | Fault determination with autonomous feature use monitoring |
US10963969B1 (en) | 2014-05-20 | 2021-03-30 | State Farm Mutual Automobile Insurance Company | Autonomous communication feature use and insurance pricing |
US10223479B1 (en) | 2014-05-20 | 2019-03-05 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature evaluation |
US11127086B2 (en) | 2014-05-20 | 2021-09-21 | State Farm Mutual Automobile Insurance Company | Accident fault determination for autonomous vehicles |
US10373259B1 (en) | 2014-05-20 | 2019-08-06 | State Farm Mutual Automobile Insurance Company | Fully autonomous vehicle insurance pricing |
US11010840B1 (en) | 2014-05-20 | 2021-05-18 | State Farm Mutual Automobile Insurance Company | Fault determination with autonomous feature use monitoring |
US11023629B1 (en) | 2014-05-20 | 2021-06-01 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature evaluation |
US10354330B1 (en) | 2014-05-20 | 2019-07-16 | State Farm Mutual Automobile Insurance Company | Autonomous feature use monitoring and insurance pricing |
US11062396B1 (en) | 2014-05-20 | 2021-07-13 | State Farm Mutual Automobile Insurance Company | Determining autonomous vehicle technology performance for insurance pricing and offering |
US11436685B1 (en) | 2014-05-20 | 2022-09-06 | State Farm Mutual Automobile Insurance Company | Fault determination with autonomous feature use monitoring |
US11386501B1 (en) | 2014-05-20 | 2022-07-12 | State Farm Mutual Automobile Insurance Company | Accident fault determination for autonomous vehicles |
US11348182B1 (en) | 2014-05-20 | 2022-05-31 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
US10974693B1 (en) | 2014-07-21 | 2021-04-13 | State Farm Mutual Automobile Insurance Company | Methods of theft prevention or mitigation |
US10540723B1 (en) | 2014-07-21 | 2020-01-21 | State Farm Mutual Automobile Insurance Company | Methods of providing insurance savings based upon telematics and usage-based insurance |
US11030696B1 (en) | 2014-07-21 | 2021-06-08 | State Farm Mutual Automobile Insurance Company | Methods of providing insurance savings based upon telematics and anonymous driver data |
US11068995B1 (en) | 2014-07-21 | 2021-07-20 | State Farm Mutual Automobile Insurance Company | Methods of reconstructing an accident scene using telematics data |
US10997849B1 (en) | 2014-07-21 | 2021-05-04 | State Farm Mutual Automobile Insurance Company | Methods of facilitating emergency assistance |
US11565654B2 (en) | 2014-07-21 | 2023-01-31 | State Farm Mutual Automobile Insurance Company | Methods of providing insurance savings based upon telematics and driving behavior identification |
US11257163B1 (en) | 2014-07-21 | 2022-02-22 | State Farm Mutual Automobile Insurance Company | Methods of pre-generating insurance claims |
US11069221B1 (en) | 2014-07-21 | 2021-07-20 | State Farm Mutual Automobile Insurance Company | Methods of facilitating emergency assistance |
US11634103B2 (en) | 2014-07-21 | 2023-04-25 | State Farm Mutual Automobile Insurance Company | Methods of facilitating emergency assistance |
US11634102B2 (en) | 2014-07-21 | 2023-04-25 | State Farm Mutual Automobile Insurance Company | Methods of facilitating emergency assistance |
US10723312B1 (en) | 2014-07-21 | 2020-07-28 | State Farm Mutual Automobile Insurance Company | Methods of theft prevention or mitigation |
US10832327B1 (en) | 2014-07-21 | 2020-11-10 | State Farm Mutual Automobile Insurance Company | Methods of providing insurance savings based upon telematics and driving behavior identification |
US10825326B1 (en) | 2014-07-21 | 2020-11-03 | State Farm Mutual Automobile Insurance Company | Methods of facilitating emergency assistance |
US10475127B1 (en) | 2014-07-21 | 2019-11-12 | State Farm Mutual Automobile Insurance Company | Methods of providing insurance savings based upon telematics and insurance incentives |
US10431018B1 (en) | 2014-11-13 | 2019-10-01 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating status assessment |
US11532187B1 (en) | 2014-11-13 | 2022-12-20 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating status assessment |
US11173918B1 (en) | 2014-11-13 | 2021-11-16 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US10824144B1 (en) | 2014-11-13 | 2020-11-03 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US10416670B1 (en) | 2014-11-13 | 2019-09-17 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US11175660B1 (en) | 2014-11-13 | 2021-11-16 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US11247670B1 (en) | 2014-11-13 | 2022-02-15 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US10353694B1 (en) | 2014-11-13 | 2019-07-16 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle software version assessment |
US10336321B1 (en) | 2014-11-13 | 2019-07-02 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US10266180B1 (en) | 2014-11-13 | 2019-04-23 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US11127290B1 (en) | 2014-11-13 | 2021-09-21 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle infrastructure communication device |
US11494175B2 (en) | 2014-11-13 | 2022-11-08 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating status assessment |
US11014567B1 (en) | 2014-11-13 | 2021-05-25 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operator identification |
US10246097B1 (en) | 2014-11-13 | 2019-04-02 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operator identification |
US11500377B1 (en) | 2014-11-13 | 2022-11-15 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US10241509B1 (en) | 2014-11-13 | 2019-03-26 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US10824415B1 (en) | 2014-11-13 | 2020-11-03 | State Farm Automobile Insurance Company | Autonomous vehicle software version assessment |
US10821971B1 (en) | 2014-11-13 | 2020-11-03 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle automatic parking |
US10943303B1 (en) | 2014-11-13 | 2021-03-09 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating style and mode monitoring |
US10940866B1 (en) | 2014-11-13 | 2021-03-09 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating status assessment |
US10166994B1 (en) | 2014-11-13 | 2019-01-01 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating status assessment |
US10915965B1 (en) | 2014-11-13 | 2021-02-09 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle insurance based upon usage |
US10831204B1 (en) | 2014-11-13 | 2020-11-10 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle automatic parking |
US10157423B1 (en) | 2014-11-13 | 2018-12-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operating style and mode monitoring |
US11645064B2 (en) | 2014-11-13 | 2023-05-09 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle accident and emergency response |
US11720968B1 (en) | 2014-11-13 | 2023-08-08 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle insurance based upon usage |
US11726763B2 (en) | 2014-11-13 | 2023-08-15 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle automatic parking |
US11740885B1 (en) | 2014-11-13 | 2023-08-29 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle software version assessment |
US11954482B2 (en) | 2014-11-13 | 2024-04-09 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control assessment and selection |
US10831191B1 (en) | 2014-11-13 | 2020-11-10 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle accident and emergency response |
US11748085B2 (en) | 2014-11-13 | 2023-09-05 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operator identification |
US10776070B2 (en) * | 2015-03-31 | 2020-09-15 | Sony Corporation | Information processing device, control method, and program |
US20180107445A1 (en) * | 2015-03-31 | 2018-04-19 | Sony Corporation | Information processing device, control method, and program |
US10262529B2 (en) | 2015-06-19 | 2019-04-16 | International Business Machines Corporation | Management of moving objects |
US10749734B2 (en) * | 2015-07-07 | 2020-08-18 | International Business Machines Corporation | Management of events and moving objects |
US10742479B2 (en) | 2015-07-07 | 2020-08-11 | International Business Machines Corporation | Management of events and moving objects |
US10742478B2 (en) | 2015-07-07 | 2020-08-11 | International Business Machines Corporation | Management of events and moving objects |
US20170012812A1 (en) * | 2015-07-07 | 2017-01-12 | International Business Machines Corporation | Management of events and moving objects |
US10977945B1 (en) | 2015-08-28 | 2021-04-13 | State Farm Mutual Automobile Insurance Company | Vehicular driver warnings |
US10748419B1 (en) | 2015-08-28 | 2020-08-18 | State Farm Mutual Automobile Insurance Company | Vehicular traffic alerts for avoidance of abnormal traffic conditions |
US11450206B1 (en) | 2015-08-28 | 2022-09-20 | State Farm Mutual Automobile Insurance Company | Vehicular traffic alerts for avoidance of abnormal traffic conditions |
US10950065B1 (en) | 2015-08-28 | 2021-03-16 | State Farm Mutual Automobile Insurance Company | Shared vehicle usage, monitoring and feedback |
US10769954B1 (en) | 2015-08-28 | 2020-09-08 | State Farm Mutual Automobile Insurance Company | Vehicular driver warnings |
US10401852B2 (en) | 2015-11-04 | 2019-09-03 | Zoox, Inc. | Teleoperation system and method for trajectory modification of autonomous vehicles |
US11106218B2 (en) | 2015-11-04 | 2021-08-31 | Zoox, Inc. | Adaptive mapping to navigate autonomous vehicles responsive to physical environment changes |
US10334050B2 (en) | 2015-11-04 | 2019-06-25 | Zoox, Inc. | Software application and logic to modify configuration of an autonomous vehicle |
US11314249B2 (en) | 2015-11-04 | 2022-04-26 | Zoox, Inc. | Teleoperation system and method for trajectory modification of autonomous vehicles |
US10712750B2 (en) | 2015-11-04 | 2020-07-14 | Zoox, Inc. | Autonomous vehicle fleet service and system |
US11301767B2 (en) | 2015-11-04 | 2022-04-12 | Zoox, Inc. | Automated extraction of semantic information to enhance incremental mapping modifications for robotic vehicles |
US11283877B2 (en) | 2015-11-04 | 2022-03-22 | Zoox, Inc. | Software application and logic to modify configuration of an autonomous vehicle |
US11067983B2 (en) * | 2015-11-04 | 2021-07-20 | Zoox, Inc. | Coordination of dispatching and maintaining fleet of autonomous vehicles |
US10248119B2 (en) | 2015-11-04 | 2019-04-02 | Zoox, Inc. | Interactive autonomous vehicle command controller |
US10446037B2 (en) | 2015-11-04 | 2019-10-15 | Zoox, Inc. | Software application to request and control an autonomous vehicle service |
US20180356821A1 (en) * | 2015-11-04 | 2018-12-13 | Zoox, Inc. | Coordination of dispatching and maintaining fleet of autonomous vehicles |
US10591910B2 (en) | 2015-11-04 | 2020-03-17 | Zoox, Inc. | Machine-learning systems and techniques to optimize teleoperation and/or planner decisions |
US11796998B2 (en) | 2015-11-04 | 2023-10-24 | Zoox, Inc. | Autonomous vehicle fleet service and system |
US10048683B2 (en) * | 2015-11-04 | 2018-08-14 | Zoox, Inc. | Machine learning systems and techniques to optimize teleoperation and/or planner decisions |
US11061398B2 (en) | 2015-11-04 | 2021-07-13 | Zoox, Inc. | Machine-learning systems and techniques to optimize teleoperation and/or planner decisions |
US20170213461A1 (en) * | 2016-01-21 | 2017-07-27 | Ford Global Technologies, Llc | System and method for vehicle group communication via dedicated short range communication |
US11625802B1 (en) | 2016-01-22 | 2023-04-11 | State Farm Mutual Automobile Insurance Company | Coordinated autonomous vehicle automatic area scanning |
US11441916B1 (en) | 2016-01-22 | 2022-09-13 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle trip routing |
US11015942B1 (en) | 2016-01-22 | 2021-05-25 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle routing |
US11022978B1 (en) | 2016-01-22 | 2021-06-01 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle routing during emergencies |
US11656978B1 (en) | 2016-01-22 | 2023-05-23 | State Farm Mutual Automobile Insurance Company | Virtual testing of autonomous environment control system |
US10545024B1 (en) | 2016-01-22 | 2020-01-28 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle trip routing |
US10156848B1 (en) | 2016-01-22 | 2018-12-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle routing during emergencies |
US11062414B1 (en) | 2016-01-22 | 2021-07-13 | State Farm Mutual Automobile Insurance Company | System and method for autonomous vehicle ride sharing using facial recognition |
US11682244B1 (en) | 2016-01-22 | 2023-06-20 | State Farm Mutual Automobile Insurance Company | Smart home sensor malfunction detection |
US10503168B1 (en) | 2016-01-22 | 2019-12-10 | State Farm Mutual Automotive Insurance Company | Autonomous vehicle retrieval |
US11719545B2 (en) | 2016-01-22 | 2023-08-08 | Hyundai Motor Company | Autonomous vehicle component damage and salvage assessment |
US10829063B1 (en) | 2016-01-22 | 2020-11-10 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle damage and salvage assessment |
US10747234B1 (en) | 2016-01-22 | 2020-08-18 | State Farm Mutual Automobile Insurance Company | Method and system for enhancing the functionality of a vehicle |
US10679497B1 (en) | 2016-01-22 | 2020-06-09 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle application |
US10579070B1 (en) | 2016-01-22 | 2020-03-03 | State Farm Mutual Automobile Insurance Company | Method and system for repairing a malfunctioning autonomous vehicle |
US11879742B2 (en) | 2016-01-22 | 2024-01-23 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle application |
US11119477B1 (en) | 2016-01-22 | 2021-09-14 | State Farm Mutual Automobile Insurance Company | Anomalous condition detection and response for autonomous vehicles |
US10324463B1 (en) | 2016-01-22 | 2019-06-18 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation adjustment based upon route |
US10134278B1 (en) | 2016-01-22 | 2018-11-20 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle application |
US10828999B1 (en) | 2016-01-22 | 2020-11-10 | State Farm Mutual Automobile Insurance Company | Autonomous electric vehicle charging |
US11124186B1 (en) | 2016-01-22 | 2021-09-21 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle control signal |
US11016504B1 (en) | 2016-01-22 | 2021-05-25 | State Farm Mutual Automobile Insurance Company | Method and system for repairing a malfunctioning autonomous vehicle |
US11136024B1 (en) | 2016-01-22 | 2021-10-05 | State Farm Mutual Automobile Insurance Company | Detecting and responding to autonomous environment incidents |
US11526167B1 (en) | 2016-01-22 | 2022-12-13 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle component maintenance and repair |
US11513521B1 (en) | 2016-01-22 | 2022-11-29 | State Farm Mutual Automobile Insurance Copmany | Autonomous vehicle refueling |
US11920938B2 (en) | 2016-01-22 | 2024-03-05 | Hyundai Motor Company | Autonomous electric vehicle charging |
US11348193B1 (en) | 2016-01-22 | 2022-05-31 | State Farm Mutual Automobile Insurance Company | Component damage and salvage assessment |
US11181930B1 (en) | 2016-01-22 | 2021-11-23 | State Farm Mutual Automobile Insurance Company | Method and system for enhancing the functionality of a vehicle |
US11189112B1 (en) | 2016-01-22 | 2021-11-30 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle sensor malfunction detection |
US10802477B1 (en) | 2016-01-22 | 2020-10-13 | State Farm Mutual Automobile Insurance Company | Virtual testing of autonomous environment control system |
US10824145B1 (en) | 2016-01-22 | 2020-11-03 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle component maintenance and repair |
US11242051B1 (en) | 2016-01-22 | 2022-02-08 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle action communications |
US10395332B1 (en) | 2016-01-22 | 2019-08-27 | State Farm Mutual Automobile Insurance Company | Coordinated autonomous vehicle automatic area scanning |
US10386845B1 (en) | 2016-01-22 | 2019-08-20 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle parking |
US11126184B1 (en) | 2016-01-22 | 2021-09-21 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle parking |
US10818105B1 (en) | 2016-01-22 | 2020-10-27 | State Farm Mutual Automobile Insurance Company | Sensor malfunction detection |
US11600177B1 (en) | 2016-01-22 | 2023-03-07 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle application |
US11440494B1 (en) | 2016-01-22 | 2022-09-13 | State Farm Mutual Automobile Insurance Company | Detecting and responding to autonomous vehicle incidents |
US10691126B1 (en) | 2016-01-22 | 2020-06-23 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle refueling |
US10295363B1 (en) | 2016-01-22 | 2019-05-21 | State Farm Mutual Automobile Insurance Company | Autonomous operation suitability assessment and mapping |
US10453342B2 (en) * | 2016-02-03 | 2019-10-22 | Volkswagen Aktiengesellschaft | Methods, devices, and computer programs for providing information about a dangerous situation on a vehicle-to-vehicle interface |
US20190043358A1 (en) * | 2016-02-03 | 2019-02-07 | Volkswagen Aktiengesellschaft | Methods, devices, and computer programs for providing information about a dangerous situation on a vehicle-to-vehicle interface |
US11610493B1 (en) * | 2016-03-22 | 2023-03-21 | Amazon Technologies, Inc. | Unmanned aerial vehicles utilized to collect updated travel related data for deliveries |
US10388082B2 (en) * | 2016-06-29 | 2019-08-20 | Volkswagen Ag | Method for spectrally efficient determination of collective environmental information for cooperative and/or autonomous driving |
US20180005460A1 (en) * | 2016-06-29 | 2018-01-04 | Volkswagen Ag | Method for spectrally efficient determination of collective environmental information for cooperative and/or autonomous driving |
US10140838B2 (en) * | 2017-03-21 | 2018-11-27 | GM Global Technology Operations LLC | Automatic transmission of reminders for devices left behind |
US20180276974A1 (en) * | 2017-03-21 | 2018-09-27 | GM Global Technology Operations LLC | Automatic transmission of reminders for devices left behind |
US20180286244A1 (en) * | 2017-03-31 | 2018-10-04 | T-Mobile U.S.A., Inc. | Managing communications between connected vehicles via a cellular network |
WO2018183950A1 (en) * | 2017-03-31 | 2018-10-04 | T-Mobile Usa, Inc. | Managing communications between connected vehicles via a cellular network |
US10548184B2 (en) * | 2017-03-31 | 2020-01-28 | T-Mobile Usa, Inc. | Managing communications for connected vehicles using a cellular network |
US11240876B2 (en) * | 2017-03-31 | 2022-02-01 | T-Mobile Usa, Inc. | Managing communications for connected vehicles using a cellular network |
US10974718B2 (en) * | 2017-03-31 | 2021-04-13 | T-Mobile Usa, Inc. | Managing communications between connected vehicles via a cellular network |
US11690133B2 (en) | 2017-03-31 | 2023-06-27 | T-Mobile Usa, Inc. | Managing communications for connected vehicles using a cellular network |
US20180286245A1 (en) * | 2017-03-31 | 2018-10-04 | T-Mobile U.S.A., Inc. | Managing communications for connected vehicles using a cellular network |
US10571285B2 (en) * | 2017-04-17 | 2020-02-25 | Ford Global Technologies, Llc | Vehicle route control |
US20180299283A1 (en) * | 2017-04-17 | 2018-10-18 | Ford Global Technologies, Llc | Vehicle Route Control |
US10339810B2 (en) | 2017-06-21 | 2019-07-02 | International Business Machines Corporation | Management of mobile objects |
US10600322B2 (en) | 2017-06-21 | 2020-03-24 | International Business Machines Corporation | Management of mobile objects |
US10585180B2 (en) | 2017-06-21 | 2020-03-10 | International Business Machines Corporation | Management of mobile objects |
US11386785B2 (en) | 2017-06-21 | 2022-07-12 | International Business Machines Corporation | Management of mobile objects |
US10168424B1 (en) | 2017-06-21 | 2019-01-01 | International Business Machines Corporation | Management of mobile objects |
US11024161B2 (en) | 2017-06-21 | 2021-06-01 | International Business Machines Corporation | Management of mobile objects |
US10504368B2 (en) | 2017-06-21 | 2019-12-10 | International Business Machines Corporation | Management of mobile objects |
US10535266B2 (en) | 2017-06-21 | 2020-01-14 | International Business Machines Corporation | Management of mobile objects |
US10540895B2 (en) | 2017-06-21 | 2020-01-21 | International Business Machines Corporation | Management of mobile objects |
US10546488B2 (en) | 2017-06-21 | 2020-01-28 | International Business Machines Corporation | Management of mobile objects |
US11315428B2 (en) | 2017-06-21 | 2022-04-26 | International Business Machines Corporation | Management of mobile objects |
US11723579B2 (en) | 2017-09-19 | 2023-08-15 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement |
DE102017218091A1 (en) * | 2017-10-11 | 2019-04-11 | Bayerische Motoren Werke Aktiengesellschaft | Method and device for updating traffic information |
US11869360B2 (en) | 2017-11-03 | 2024-01-09 | International Business Machines Corporation | Empathic autonomous vehicle |
US11151883B2 (en) * | 2017-11-03 | 2021-10-19 | International Business Machines Corporation | Empathic autonomous vehicle |
US10498685B2 (en) * | 2017-11-20 | 2019-12-03 | Google Llc | Systems, methods, and apparatus for controlling provisioning of notifications based on sources of the notifications |
US11717686B2 (en) | 2017-12-04 | 2023-08-08 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement to facilitate learning and performance |
US11318277B2 (en) | 2017-12-31 | 2022-05-03 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement to enhance emotional response |
US11273283B2 (en) | 2017-12-31 | 2022-03-15 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement to enhance emotional response |
US11478603B2 (en) | 2017-12-31 | 2022-10-25 | Neuroenhancement Lab, LLC | Method and apparatus for neuroenhancement to enhance emotional response |
US11893793B2 (en) | 2018-03-28 | 2024-02-06 | Gal Zuckerman | Facilitating service actions using random imagery data captured by a plurality of on-road vehicles |
US11206375B2 (en) | 2018-03-28 | 2021-12-21 | Gal Zuckerman | Analyzing past events by utilizing imagery data captured by a plurality of on-road vehicles |
US11364361B2 (en) | 2018-04-20 | 2022-06-21 | Neuroenhancement Lab, LLC | System and method for inducing sleep by transplanting mental states |
US11138418B2 (en) | 2018-08-06 | 2021-10-05 | Gal Zuckerman | Systems and methods for tracking persons by utilizing imagery data captured by on-road vehicles |
US10997853B2 (en) * | 2018-08-10 | 2021-05-04 | Honda Motor Co., Ltd. | Control device and computer readable storage medium |
US20200051427A1 (en) * | 2018-08-10 | 2020-02-13 | Honda Motor Co.,Ltd. | Control device and computer readable storage medium |
US11452839B2 (en) | 2018-09-14 | 2022-09-27 | Neuroenhancement Lab, LLC | System and method of improving sleep |
WO2020089039A1 (en) * | 2018-10-29 | 2020-05-07 | Robert Bosch Gmbh | Method for the vehicle-based verification of at least one detected dangerous place |
US11474518B2 (en) * | 2019-05-13 | 2022-10-18 | International Business Machines Corporation | Event validation using multiple sources |
US11669071B2 (en) | 2020-01-08 | 2023-06-06 | International Business Machines Corporation | Organizing a temporary device group for collaborative computing |
US20210225092A1 (en) * | 2020-01-16 | 2021-07-22 | Ford Global Technologies, Llc | Method and apparatus for one to many vehicle broadcast handling |
US20230045241A1 (en) * | 2021-08-03 | 2023-02-09 | GM Global Technology Operations LLC | Remote observation and reporting of vehicle operating condition via v2x communication |
US11875611B2 (en) * | 2021-08-03 | 2024-01-16 | GM Global Technology Operations LLC | Remote observation and reporting of vehicle operating condition via V2X communication |
DE102022206506A1 (en) | 2022-06-28 | 2023-12-28 | Volkswagen Aktiengesellschaft | Method for setting up a virtual ad hoc network and central data processing device |
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