EP3147882A1 - System und verfahren für ein intelligentes transportsystem - Google Patents

System und verfahren für ein intelligentes transportsystem Download PDF

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Publication number
EP3147882A1
EP3147882A1 EP15186413.9A EP15186413A EP3147882A1 EP 3147882 A1 EP3147882 A1 EP 3147882A1 EP 15186413 A EP15186413 A EP 15186413A EP 3147882 A1 EP3147882 A1 EP 3147882A1
Authority
EP
European Patent Office
Prior art keywords
vehicle
vehicles
traffic
determining
traffic light
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP15186413.9A
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English (en)
French (fr)
Inventor
Pawel Michal Malinowski
Jozef Szczepan Suchy
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Akademia Gomiczo Hutnicza
Original Assignee
Akademia Gomiczo Hutnicza
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Akademia Gomiczo Hutnicza filed Critical Akademia Gomiczo Hutnicza
Publication of EP3147882A1 publication Critical patent/EP3147882A1/de
Withdrawn legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
    • G08G1/096716—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information does not generate an automatic action on the vehicle control
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096733—Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place
    • G08G1/096758—Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place where no selection takes place on the transmitted or the received information
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
    • G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station

Definitions

  • the present invention relates to a system and a method for an intelligent transportation system (ITS).
  • ITS intelligent transportation system
  • the present invention relates to monitoring of traffic conditions and recommending optimal speeds for different vehicles present in proximity to an intersection where traffic lights have been installed.
  • the system is applicable in a so called Smart City concept implementation.
  • ITSs Intelligent Transportation Systems
  • information and communication technologies are applied in the field of road transport, including transportation system infrastructure, appropriately equipped vehicles and trained users, and in traffic and mobility management, as well as for interfaces with other modes of transport.
  • ITSs are implemented by using different technologies to monitor traffic, such as car navigation, traffic signal control systems, variable message road signs, automatic number plate recognition or speed cameras. Frequently, ITS implementations monitor traffic in real-time and use data obtained from other sources, such as parking guidance and information systems, weather information and the like. In more sophisticated ITSs, there may be employed predictive techniques that are aimed at modeling and comparison with historical traffic data. This arrangement typically requires devices installed in vehicles, as well as a distributed or a centralized ITS server system. The server processes much more data that typical client devices installed in cars. ITS may employ three kinds of communication, which may be combined together: (a) vehicle-vehicle, (b) vehicle-infrastructure and (c) infrastructure-vehicle.
  • a US patent US5519390 discloses a traffic light timer, which provides a visible and accurate warning that a traffic light signal is about to change.
  • the time remaining before the change is displayed in numeric form on a display and visibly counts down the seconds remaining.
  • the display can be alphanumeric or graphical, allowing for the display of free form icons.
  • Such timer may allow the driver to adapt the speed of travel to drive optimally, i.e. to slow down when the driver assumes that the light will soon change to red, or to speed up when the driver assumes that there is sufficient time to cross the road at green light.
  • the drawback of the system is that it requires the driver to make own assessments and that it is effective only within the range of the eyesight of the driver.
  • a US patent application US20130110371 discloses a driving assisting apparatus that assists in driving a vehicle and includes: a vehicle speed sensor that detects a vehicle speed of the vehicle; a control unit that determines a recommended traveling state based on a current vehicle speed detected by the vehicle speed sensor and at least one of an accelerated vehicle speed when the vehicle accelerates from the current vehicle speed at an allowable acceleration and a decelerated vehicle speed when the vehicle decelerates from the current vehicle speed at an allowable deceleration; and an assisting unit that assists in driving the vehicle based on the recommended traveling state determined by the control unit.
  • a driving assisting apparatus can assist a vehicle to pass through a traffic light location if the color of the traffic light is green when the vehicle arrives at the traffic light location by accelerating from the current vehicle speed at a predetermined acceleration or when the vehicle arrives at the traffic light location by decelerating from the current speed at a predetermined deceleration.
  • the information required for calculating the target vehicle speed range includes the infrastructure information including the lighting cycle and the traffic light change time of the traffic light, through which the vehicle will pass, the information on the current position of the vehicle required for calculating the distance between the vehicle and the traffic light, and the map information including the position information on the traffic light.
  • the aim of the development of the present invention is an improved method and apparatus for a system and method for an intelligent transportation system.
  • the object of the invention is a method for an intelligent transportation system, the method comprising the steps of: reading a vehicle's geolocation and determining a direction of its movement; determining the closest traffic light based on the vehicles position and direction of movement; determining a distance between the vehicle and the closest traffic light; determining the closest traffic light's phase and its remaining time; determining a number of vehicles in the group of vehicles between the vehicle and the closest traffic light; and based on the aforementioned data, calculating an optimum vehicle speed and transmitting the result of this calculation to the vehicle.
  • a distance traveled by each of these vehicles in a given amount of time is taken into account in the calculating step.
  • determining vehicles' count between the vehicle and the closest traffic light further comprises determining a distance traveled by each of these vehicles in a given amount of time.
  • the step of calculating an optimum vehicle speed takes into account statistical data related to leaving this particular intersection by vehicles.
  • the reading step further comprises a step of reading a vehicle's route.
  • the step of reading is executed for a plurality of vehicles and based on the received route of each vehicle, calculating traffic conditions in the future.
  • the invention is also related to a computer program comprising program code means for performing all the steps of the computer-implemented method as defined above when said program is run on a computer, as well as to a computer readable medium storing computer-executable instructions performing all the steps of the computer-implemented method as defined above when executed on a computer.
  • Another object of the invention is a system for an intelligent transportation system, the system comprising: a traffic lights system providing data regarding geolocation and phases of traffic lights; a traffic monitoring system configured to determine how many vehicles there are between a given vehicle and a given traffic light; a data processing server communicatively connected with client systems present in vehicles each client system comprising a geolocation module configured to provide information on vehicle's location; and wherein the data processing server is configured to execute all steps of the method as defined above.
  • these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system.
  • these signals are referred to as bits, packets, messages, values, elements, symbols, characters, terms, numbers, or the like.
  • a computer-readable (storage) medium typically may be non-transitory and/or comprise a non-transitory device.
  • a non-transitory storage medium may include a device that may be tangible, meaning that the device has a concrete physical form, although the device may change its physical state.
  • non-transitory refers to a device remaining tangible despite a change in state.
  • example means serving as a non-limiting example, instance, or illustration.
  • terms "for example” and “e.g.” introduce a list of one or more non-limiting examples, instances, or illustrations.
  • Fig. 1 presents a diagram of the system according to the present invention.
  • the system comprises a traffic lights system 101, preferably synchronized using a GPS time.
  • the traffic lights system 101 provides data regarding geolocation and phases of traffic lights.
  • a corresponding database 102 stores, per each traffic light, a geolocation, current phase (green, yellow, red, pulsing yellow) as well as remaining duration of the current phase and programmed subsequent phases.
  • the phases may be programmed by the respective ITS system depending on a traffic present on lane(s) to which the respective traffic light is assigned.
  • An exemplary record of the database 102, describing a particular traffic light, may have the following contents:
  • the record further specifies that the traffic light operates in a loop wherein a red phase lasts 60s, the subsequent yellow phase lasts 4s, while a subsequent green phase lasts 25s and is followed by a yellow phase of 4s.
  • the system further comprises a traffic monitoring subsystem 103 configured to determine how many vehicles there are between a given vehicle and a given traffic light (in general, an intersection). This may be achieved by analyzing a geolocation signal received from each of passing vehicles or the data may be obtained via other detection means, such as CCTV cameras combined with image processing and object detection or Inductive loop detection or Bluetooth detection. Alternatively, more than one method of vehicles detection may be employed in order to obtain more accurate results.
  • a traffic monitoring subsystem 103 configured to determine how many vehicles there are between a given vehicle and a given traffic light (in general, an intersection). This may be achieved by analyzing a geolocation signal received from each of passing vehicles or the data may be obtained via other detection means, such as CCTV cameras combined with image processing and object detection or Inductive loop detection or Bluetooth detection. Alternatively, more than one method of vehicles detection may be employed in order to obtain more accurate results.
  • the traffic monitoring system 103 is not only aware of how many vehicles there are in a given area, but the system is also aware which vehicles these are and has a capability of selectively communicating with these vehicles. Visual information from the traffic monitoring system 103 may aid a traffic management centre to take actions in real time.
  • Both the traffic lights system 101 and the traffic monitoring system 103 are connected to a data processing server 104, which also communicates with client systems present in vehicles 105.
  • client system comprises a geolocation module 106 providing constant information on vehicle's location (eg. GPS) as well as a driving assist system 107 providing information to a driver.
  • the information provided by the driving assist system 107 is received from the server 104 and preferably presented on a display screen.
  • the client system may have a form of a navigation system installed on board of a vehicle, or a portable device, such as a tablet or a smartphone.
  • the client system 105 comprises a data interface for communicating with the data interface of the server via a communication link.
  • the communication may be effected via a dedicated communication channel, or via standard communication channels, such as the Internet.
  • Each client device may also be configured to operate as a video recorder of what is happening in front of a vehicle in which the client device is installed.
  • Information about the registered event, along with its detailed localization, can be transferred to another entity, for example to police information system (for example, to the nearest police station) by one-click action.
  • Each vehicle's client system sends geolocation data to the data processing server 104, which after traffic analysis determines traffic between the vehicles location and the next intersection (traffic lights).
  • Traffic factors include vehicle presence as such, traffic flow rate (per unit of time), traffic occupancy and density, traffic speed, vehicle headway, and traffic queue length.
  • This information is used to optimize speed recommendation for the vehicle.
  • the data processing server 104 may create a map of traffic with respect to existing map (for example a city map). This allows for a constant traffic monitoring.
  • Each vehicle may have an associated route it follows, while statistical data per vehicle and/or per traffic state at a given time and date may be used to predict traffic in the future e.g. in 5, 10, 15 minutes.
  • the traffic map also allows the data processing server 104 to determine an optimized route for each given vehicle, based on current traffic conditions as well as predicted traffic conditions.
  • the system may be extended with an addition of a parking lots monitoring system 108 providing a database of free parking spaces comprising geolocation of the parking spaces (free and/or occupied). Each parking space may be automatically monitored by a suitable sensor that would update its information in the database once it becomes free or occupied.
  • the parking lots monitoring system 108 sends to the server 104 information about free parking spaces.
  • the server 104 analyzes the current position of the vehicle and determines the path to the nearest free parking space, which has simultaneously its status changed to "reserved" - therefore, the system 104 will not propose this parking space to other vehicles.
  • the system may also comprise a public transportation system database 109 providing information on stops and schedules of public transport. This may be beneficial in case of heavy traffic, a user may be recommended a route including public transport instead of a car. Owing to the aforementioned traffic map, a user planning a route may be advised not to take a car in certain conditions of traffic.
  • the public transportation system 109 comprises a database of information about paths of public transportation vehicles, their stops and locations, communication nodes wherein a passenger may change transport means, detailed schedule of arrivals and departures.
  • the information is sent to the server 104, which may analyze the time of travel by car and by the public transportation vehicles to the destination, taking into account current traffic and the predicted time of transport by public transportation - and suggest the user with the fastest transport means.
  • Fig. 2 presents a diagram of the method according to the present invention.
  • the method starts at step 201 to read vehicle's geolocation and determine direction of its movement. This information is received from a client device installed in a particular vehicle.
  • the direction of movement may be determined from vehicle's navigation system or determined based on a change in geolocation of the vehicle over a period of time.
  • the data processing system 104 determines the closest traffic light, with respect to the vehicle, based on the data from the traffic lights system 101. In order to determine that, a vehicles position and direction of movement is taken into account.
  • the server 104 determines a distance between the vehicle and the closest traffic light. This may take into account a map of roads available to the data processing server 104 and a suitable distance calculation module based on coordinates of two points of the respective map.
  • the data processing server 104 determines the closest traffic light's phase and its remaining time in order to lastly determine 205 the number of vehicles between the vehicle and the closest traffic light (while traveling on a selected route).
  • the data processing server 104 determines the closest traffic light's phase and its remaining time in order to lastly determine 205 the number of vehicles between the vehicle and the closest traffic light (while traveling on a selected route).
  • the number of vehicles is taken into account but also a distance traveled by each of these vehicles in a given amount of time.
  • the monitored amount of time may be different depending on distance between the vehicle and the closest traffic light.
  • the data processing server 104 calculates 206 an optimum vehicle speed and transmits the result of this calculation to the vehicle at step 207.
  • transmission to the client device of a vehicle may also comprise a time stamp defining the time, at which it has been generated.
  • the client device may then determine a time lag between the time at which the information was generated at the server 104 and at which was actually processed by the client 105. This may not be required in an embodiment, when the server and the clients are synchronized for example with a GPS time.
  • Fig. 3 presents an example of a user interface wherein item 301 indicates traffic light phase as well as a recommended speed for the vehicle depending on a selected road lane.
  • Item 302 presents another example showing a recommended vehicle speed as well as traffic light phase and timeout of the respective traffic light phases.
  • the first example is a case taking into account current traffic based on geolocation of other vehicles.
  • Each vehicle comprises a client system 105 running an appropriate software and having access to its geolocation (typically a smartphone).
  • the device also communicates with a server (typically via the Internet).
  • the server 104 comprises a database of geolocations of traffic lights and information on traffic lights phases for each road lane.
  • a vehicle joining traffic cyclically transmits its geolocation (A) to the server 104.
  • the server 104 receives geolocations of other vehicles and associates these geolocations with a traffic map.
  • the system analyzes geolocation of vehicle A and its distance from traffic lights B, the traffic light phases, taking into account speed of other vehicles on a given section of the road as well as statistical data related to leaving this particular intersection by vehicles.
  • the server 104 calculates optimum speed, not higher that a maximum allowed speed, and transmits a result of the calculation to the vehicle A.
  • the aforementioned is executed cyclically, for example every few seconds. This will allow to keep the amount of transmitted data at reasonable and acceptable levels.
  • the device of the vehicle may also receive data on traffic lights and phase so that it displays the closest traffic lights states e.g. colors and times of phases. This also improves safety as it happens that a vehicle stopped at a traffic light is so positioned that a driver does not see the lights or it is difficult for the driver to look at the lights.
  • the second implementation example of the present invention includes traffic prediction in near future.
  • Each client system present in vehicles 105 comprises a programmed route the driver will follow. This route, associated with the vehicle, is transmitted to the server 104. All other data transmitted to the server 104 in case of example number one are also transmitted to the server 104 in the example number two.
  • the server 104 calculates an average speed for each vehicle on a given road section, based on geolocation of each vehicle, current speed of each vehicle, current traffic on the road section, transmitted vehicles' routes.
  • the server also may calculate a time of arrival at a destination based on calculated speed, distance, traffic lights phases as well as traffic flow rates at different intersections.
  • the server 104 may calculate traffic conditions in the near future e.g. 5, 10 or 15 minutes. Having access to this information, routes of vehicles may selectively be recalculated and alternative routes may be suggested for selected vehicles based on the predicted traffic conditions in the near future. For example, when traffic flow close to zero is detected at an intersection, while vehicles are standing in front of it, it may be an indicator that there is an accident and the intersection is blocked. In such cases alternative routes may be quickly advised.
  • the system according to the present invention may be implemented not only in cities but also on highways, suburban roads and other roads between cities. This in turn would allow for implementing a country-wide ITS.
  • the present invention optimizes traffic and provides useful information to drivers who may adjust their driving style and thereby save fuel. Therefore, the invention provides a useful, concrete and tangible result. Further, the present invention has been implemented as an ITS client-server system, which processes traffic information in order to recommend driving behavior. Thus, the machine or transformation test is fulfilled and that the idea is not abstract.
  • the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit", "module” or "system”.
  • the present invention may take the form of a computer program product embodied in any tangible medium of expression having computer usable program code embodied in the medium.
  • the aforementioned method for an intelligent transportation system may be fully or partially performed and/or controlled by one or more computer programs.
  • Such computer programs are typically executed by utilizing the computing resources in a computing device.
  • Applications are stored on a non-transitory medium.
  • An example of a non-transitory medium is a non-volatile memory, for example a flash memory while an example of a volatile memory is RAM.
  • the computer instructions are executed by a processor.
  • These memories are exemplary recording media for storing computer programs comprising computer-executable instructions performing all the steps of the computer-implemented method according the technical concept presented herein.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Atmospheric Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Traffic Control Systems (AREA)
EP15186413.9A 2015-09-22 2015-09-23 System und verfahren für ein intelligentes transportsystem Withdrawn EP3147882A1 (de)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PL414042A PL414042A1 (pl) 2015-09-22 2015-09-22 Inteligentny system transportowy i sposób wykorzystania inteligentnego systemu transportowego

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EP3147882A1 true EP3147882A1 (de) 2017-03-29

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107331182A (zh) * 2017-07-13 2017-11-07 北京航空航天大学 一种面向连续信号交叉口的网联环境下自动驾驶车速控制方法
CN110228479A (zh) * 2019-05-27 2019-09-13 武汉理工大学 一种考虑驾驶员驾驶风格的车速引导方法
EP3905218A1 (de) * 2020-04-27 2021-11-03 Volkswagen Aktiengesellschaft Verfahren und system zum bereitstellen von karten- und spat-nachrichten für einen neu eingerichteten satz von mindestens einer ampel
DE102021001802A1 (de) 2021-04-08 2022-10-13 Abdullatif Alhaj Rabie Smart-Ampelsystem im Auto, Smart-Ampelsystem in der Straße
WO2024081192A1 (en) * 2022-10-14 2024-04-18 Motional Ad Llc Optimizing alerts for vehicles experiencing stuck conditions

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111932893B (zh) * 2020-08-25 2022-07-05 上海宝康电子控制工程有限公司 基于信号与电警数据融合技术实现路段状态研判处理的方法

Citations (6)

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Publication number Priority date Publication date Assignee Title
US5519390A (en) 1995-02-02 1996-05-21 Casini; Peter Traffic light timer
DE102009042923A1 (de) * 2009-09-24 2011-08-04 Siemens Aktiengesellschaft, 80333 Fahrerassistenzsystem
DE102010052702A1 (de) * 2010-11-26 2012-05-31 Audi Ag Verfahren zur Steuerung einer Lichtsignalanlage und zugehörige Lichtsignalanlage
DE102012006708A1 (de) * 2012-03-29 2012-10-18 Daimler Ag Kraftfahrzeug, mit dem eine optimale Durchschnittsgeschwindigkeit zum Erreichen eines grünen Lichtzeichens einer Lichtzeichenanlage empfangbar ist
US20130110371A1 (en) 2011-11-01 2013-05-02 Yuki Ogawa Driving assisting apparatus and driving assisting method
WO2013109472A1 (en) * 2012-01-17 2013-07-25 On Time Systems, Inc. Driver safety enhancement using intelligent traffic signals and gps

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5519390A (en) 1995-02-02 1996-05-21 Casini; Peter Traffic light timer
DE102009042923A1 (de) * 2009-09-24 2011-08-04 Siemens Aktiengesellschaft, 80333 Fahrerassistenzsystem
DE102010052702A1 (de) * 2010-11-26 2012-05-31 Audi Ag Verfahren zur Steuerung einer Lichtsignalanlage und zugehörige Lichtsignalanlage
US20130110371A1 (en) 2011-11-01 2013-05-02 Yuki Ogawa Driving assisting apparatus and driving assisting method
WO2013109472A1 (en) * 2012-01-17 2013-07-25 On Time Systems, Inc. Driver safety enhancement using intelligent traffic signals and gps
DE102012006708A1 (de) * 2012-03-29 2012-10-18 Daimler Ag Kraftfahrzeug, mit dem eine optimale Durchschnittsgeschwindigkeit zum Erreichen eines grünen Lichtzeichens einer Lichtzeichenanlage empfangbar ist

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107331182A (zh) * 2017-07-13 2017-11-07 北京航空航天大学 一种面向连续信号交叉口的网联环境下自动驾驶车速控制方法
CN110228479A (zh) * 2019-05-27 2019-09-13 武汉理工大学 一种考虑驾驶员驾驶风格的车速引导方法
CN110228479B (zh) * 2019-05-27 2020-12-22 武汉理工大学 一种考虑驾驶员驾驶风格的车速引导方法
EP3905218A1 (de) * 2020-04-27 2021-11-03 Volkswagen Aktiengesellschaft Verfahren und system zum bereitstellen von karten- und spat-nachrichten für einen neu eingerichteten satz von mindestens einer ampel
DE102021001802A1 (de) 2021-04-08 2022-10-13 Abdullatif Alhaj Rabie Smart-Ampelsystem im Auto, Smart-Ampelsystem in der Straße
WO2024081192A1 (en) * 2022-10-14 2024-04-18 Motional Ad Llc Optimizing alerts for vehicles experiencing stuck conditions

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