GB2596093A - An adaptive map streaming system for autonomous vehicle(s) and method thereof - Google Patents
An adaptive map streaming system for autonomous vehicle(s) and method thereof Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
- G01C21/32—Structuring or formatting of map data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
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Abstract
An adaptive map streaming system 100 and method for continuous streaming of map data from a central map database 106 to an autonomous vehicle(s) 102 through a network quality adaptive map provider unit 104. The system 100 allows the network quality adaptive map provider unit 104 to constantly query the central map database 106, the expected network coverage along the autonomous vehicle(s)s 102 scheduled route. Further the system 100 allows the network quality adaptive map provider unit 104 to select a portion of map data to be streamed to the autonomous vehicle(s) 102 based at least on one of current position of the autonomous vehicle(s) 102, upcoming route for selected destination and network quality on said route and send the selected portion of the map data to the autonomous vehicle(s) 102 via the network quality adaptive map provider unit 104.
Description
AN ADAPTIVE MAP STREAMING SYSTEM FOR AUTONOMOUS VEHICLE(S)
AND METHOD THEREOF
[0001] PREAMBLE TO THE DESCRIPTION
[00021 The following specification particularly describes the invention and the manner in which it is to be performed:
[0003] TECHNICAL FIELD
[0004] The present subject matter is related, in general to adaptive map streaming for autonomous vehicle(s). More particularly, the subject matter relates to a system for more reliable streaming of map updates from a Central Map System to an autonomous vehicle(s) (AV) while being subject to fluctuating network quality.
[0005] BACKGROUND OF THE DISCLOSURE
[0006] AVs may require high-definition maps of the road network they drive on, to be able to operate. Since these digital maps are very large in size, may need regular updates to reflect changes in the real road network, and shall he centrally manageable for a fleet of AV's, they cannot he stored inside the AV.
[0007] Therefore, a central map system is established external to the vehicle(s) at a remote location where data storage space is larger and cheaper than in the AV and data can he centrally maintained. The central map system contains a map database which stores all map information. As part of that map information, high-definition maps of the supported area of the road network are stored as a high-definition road map layer.
[0008] However, in order to he able to move forward, the AV needs to have the map section locally available which models the immediate environment along the route to be followed. Therefore, a cellular network connection between the AV and the central map system is required. Accordingly, the central map system contains a map streaming unit that can exchange information with an autonomous vehicle(s) using cellular network.
[0009] Furthermore, the AV contains a backend communication unit which gets the AV's current location and desired route from the AV and continuously sends this data via cellular network signal to the central map streaming unit. The map streaming unit then queries from the high-definition road map layer the adjacent section that is relevant for the immediate operation of the AV. The map streaming unit then sends this data via cellular network signal back to the AV's backend communication unit, enabling the AV to drive on this transmitted map area.
IS
[0010] As the exchange of information between the AV and the central map system takes place using cellular networks, this connection is subject to limited data transfer bandwidth and location dependent availability. Thus, in an event, if the signal strength of the cellular network is found to be very weak or zero at a particular location, the backend communication unit may not be able to provide the AV's location anymore to the map streaming unit and, in return, the backend communication unit will stop receiving map updates from the map streaming unit. In such a case, to avoid potentially hazardous driving situations without sufficient data about the environment, the AV may need to come to halt, unless the signal resumes.
[0011] Therefore, there exists a need for a technology that ensures that at all times the AV has a map area of the immediate region along the route locally available, even when the cellular signal strength is occasionally very weak or zero.
[0012] SUMMARY OF THE DISCLOSURE
[0013] The present disclosure overcomes one or more shortcomings of the prior art and provides additional advantages discussed throughout the present disclosure. Additional features and advantages are realized through the techniques of the present disclosure. Other embodiments and aspects of the disclosure are described in detail herein and are considered a part of the claimed disclosure.
[0014] In one non-limiting embodiment of the present disclosure, an adaptive map streaming system for continuous streaming of map data to autonomous vehicle(s) is disclosed. Said system discloses having a backend communication unit and a network quality monitoring unit placed inside the autonomous vehicle(s) and operatively coupled to each other. Said network quality monitoring unit being configured to perpetually monitor the network quality for each geographical location through which the vehicle(s) passes during a scheduled route. The system further discloses having a central map database placed external to the vehicle(s) at a distant location and configured to be communicably connected to the autonomous vehicle(s). In an aspect, the central map database not only includes a high definition road map of a location and further comprises a HD road layer unit configured to provide a high definition map of the road network for the scheduled route and a cellular network quality layer unit containing information about network quality and availability of each location on the scheduled route. The system further discloses having a network quality adaptive map provider unit located outside the autonomous vehicle(s). Said autonomous vehicle(s) is configured to connect the central map database with the backend communication unit of the autonomous vehicle(s). The network quality adaptive map provider unit is further configured to query along the autonomous vehicle(s) scheduled route the expected network coverage from the cellular network quality layer unit and the corresponding map sections from the HD road layer unit and in response predict how much new map data is to be streamed to the autonomous vehicle(s).
[0015] In another non-limiting embodiment of the present disclosure, the central map database is configured to: (i) constantly receive, from the network quality adaptive map provider unit, location information and the destination information of the autonomous vehicle(s) and (ii) in response provide the portion of detailed route map for the selected destination to assist vehicle(s) navigate, even when the autonomous vehicle(s) passes through an area with no or limited network availability.
[0016] In still another non-limiting embodiment of the present disclosure, the network quality monitoring unit, placed inside the autonomous vehicle(s), is configured to share the network quality retrieved for each geographical location through which the vehicle(s) passes during the scheduled route with the cellular network quality layer unit via the network quality adaptive map provider unit.
[0017] In yet another non-limiting embodiment of the present disclosure, the system comprises an update unit that is configured to retrieve, from the network quality monitoring unit, the network quality throughout the scheduled route and share said information with the cellular network quality layer unit to keep the cellular network quality layer updated.
[0018] In yet another non-limiting embodiment of the present disclosure the update unit is placed external to the autonomous vehicle(s) and forms a part of either the network quality adaptive map streaming unit or the cellular network quality layer unit.
[0019] in still another non-limiting embodiment of the present disclosure, the update unit is placed external to the vehicle(s) and may form a part of either the network quality mapping unit or the network quality adaptive map streaming unit.
[0020] In yet another non-linaiting embodiment of the present disclosure, the central map database is configured to store high definition digital map's of the road network for a larger geographical location.
[0021] In another non-limiting embodiment of the present disclosure, a method for continuous streaming of map data to autonomous vein cle(s)s is disclosed. The method comprising the steps of querying the central map database about the expected network coverage along the autonomous vehicle(s) scheduled route. Said method further comprises selecting a portion of map data to be streamed to the network quality adaptive map provider unit based at least on one of current position of the autonomous vehicle(s), upcoming route for selected destination and network quality on said route. As final step the method discloses sending the selected portion of the map data to the autonomous vehicle(s) via the network quality adaptive map provider unit.
[0022] In yet another non-limiting embodiment of the present disclosure, the method further comprises the steps of receiving at the central map database location information and the destination information of the autonomous vehicle(s) and sending to the autonomous vehicle(s) via the network quality adaptive map provider unit the portion of detailed route map for the selected destination to assist the autonomous vehicle(s) in navigating even when the autonomous vehicle(s) passes through an area with no or limited network.
[0023] In still another non-limiting embodiment of the present disclosure, said method further comprise updating the central map database with network availability and quality information for each geographical location present on the central map database.
[0024] The foregoing summary is illustrative only and is not intended to he in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
[0025] BRIEF DESCRIPTION OF THE DRAWINGS
[0026] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the S description, serve to explain the disclosed embodiments. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which: [0027] Figure IA depicts an exemplary block diagram of an adaptive map streaming system for continuous streaming of map data to an autonomous vehicle(s) in accordance with some embodiments of the present disclosure; [0028] Figure 1B depicts another exemplary block diagram of an adaptive map streaming system for continuous streaming of map data to an autonomous vehicle(s) in accordance with some embodiments of the present disclosure; [0029] Figure 1C depicts an exemplary central map database showing network strengths over a large geographical location, in accordance with some embodiments of the present disclosure; [0030] Figure 2 depicts a flowchart of an exemplary method for continuous streaming of map data to an autonomous vehicle(s) in accordance with some embodiments of
the present disclosure;
[0031] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.
f00321 DETAILED DESCRIPTION
[0033] In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
[0034] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.
[01135] The terms "comprises", "comprising", "include(s)", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, system or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system or method. In other words, one or more elements in a system or apparatus proceeded by "comprises... a" does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus. In the present disclosure the terms autonomous vehicle(s), vehicle(s) and AV may be used interchangeably without departing from the scope of the present application.
[0036] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
[0037] The present disclosure addresses the shortcomings of the conventional art and proposes an adaptive map streaming system and method for continuous streaming of map data to autonomous vehicle(s)(s). The system proposed in the present application allows an autonomous vehicle(s)to interact constantly with a central map database placed external to the vehicle(s) using cellular connectivity and exchange information about one of network quality, network availability for a scheduled route and in response receive HD route map for the scheduled route, even when there is no or less network coverage. In particular, the proposed system allows the autonomous vehicle(s) to interact with the central map database via a network quality adaptive map provider unit placed outside the autonomous vehicle(s)(s). The network quality adaptive map provider unit may interact with the autonomous vehicle(s) through a backend communication unit installed inside the autonomous vehicle(s)(s). The system further includes a cellular network quality layer unit being operatively connected to the central map database. Said network quality layer unit contains the network quality and availability information for the road networks stored. Further, the network quality layer unit may be configured to constantly update the central map database with network availability and quality information for each geographical location present on the central map database via information received from a network monitoring unit placed inside the autonomous vehicle(s). Further the system discloses that the network quality adaptive map providing unit may be configured to query along the autonomous vehicle(s)s scheduled route the expected network coverage from the cellular network quality layer unit and the corresponding map sections from a HD road layer unit and in response predict how much new map data is to be streamed to the autonomous vehicle(s).
[0038] Figures IA and IB depicts two exemplary embodiments of an adaptive map streaming system 100 for continuous streaming of map data to autonomous vehicle(s) 102 in accordance with some embodiments of the present disclosure.
[0039] In particular, figure IA discloses an illustrative embodiment of the system 100 comprising a vehicle(s) 102 and a central map database 106, being placed outside the vehicle(s) 102, interacting with each other. In a preferred embodiment, the vehicle(s) 102 is an autonomous vehicle(s) 102. Said autonomous vehicle(s) 102 being configured to include a backend communication unit 116 having cellular connectivity and a network quality monitoring unit 114. The system 100 further proposes having a network quality adaptive map provider unit 104, placed outside the autonomous vehicle(s) 102. In an embodiment, the network quality adaptive map provider unit 104 is the one that shares a scheduled route information of the autonomous vehicle(s) 102 with the central map database 106 and in response provides updated route map's, retrieved from the central map database 106 (discussed in detail below) to an electronic control unit (not shown) of the autonomous vehicle(s) 102 for navigation purpose.
[0040] It may he appreciated that the autonomous vehicle(s) 102 requires high-definition map's of road network they drive on to be able to operate. In addition, the autonomous vehicle(s) 102 requires a constant update on road network for the scheduled route to operate. hi an exemplary embodiment, by constant updates one may include at least one of traffic conditions on scheduled route, radius of curvature for the upcoming turns, width of the road and like conditions that are vital for the autonomous vehicle(s) 102 to operate. Further, it shall be appreciated that said map data is so large that it cannot be stored within the vehicle(s) 102 and is required to be stored at some location external to the vehicle(s) 102 that can withstand large capacity data. However, it is more important to understand that the autonomous vehicle(s) 102 requires constant update on road network, which may not be possible if the route map of a particular geographical location is stored external to vehicle(s) 102, unless a constant update of the route map is being provided to vehicle(s)102.
[0041] Figure 1A further discloses the central map database 106 comprising a cellular network quality layer unit 110 and a HD route layer unit 108 that circumvents the above problems (discussed in detail below). In particular, as shown in figure IA the system 100 includes the central map database 106 placed external to the vehicle(s) 102 at a distant location. In an exemplary embodiment, said central map database 106 may be placed at a remote location from the autonomous vehicle(s) 102 and is configured to include a detailed digital route map of a larger geographical area. In another exemplary embodiment, the central map database 106 may be configured to include digital route map of multiple neighboring cities where the vehicle(s) is registered or even for the entire country.
[0042] Figure 1A further discloses having a two-way interaction between the autonomous vehicle(s) 102 and the central map database 106. Precisely, figure IA illustrates that the autonomous vehicle(s)102 and the and the central map database 106 are communicably connected with each other to exchange route map data through network quality adaptive map provider unit 104. In an exemplary embodiment, the vehicle(s) 102, the network quality adaptive map provider unit 104 and the central map database 106 may be communicably connected to each other using cellular connectivity. Thus, it must be appreciated that the vehicle(s) 102, the network quality adaptive map provider unit 104 and the central map database 106 are equipped with GSM, CDMA or like communication technologies.
[0042] As discussed above the network quality adaptive map provider unit 104 and the central map database 106 are communicably connected to each other for the exchange of information including map data. Precisely the central map database 106 may be configured to constantly receive, from the network quality adaptive map provider unit 104, location information and the destination information of the vehicle(s) 102. In an exemplary aspect, the vehicle(s) 102 may be configured to share the location information and the destination information with the central map database 106 via the backend communication unit 116 of the vehicle(s) 102.
[0043] In response to receiving said information, the central map database 106 may be configured to provide the portion of detailed route map for the selected destination to assist vehicle(s) 102 to navigate. The process of sending portion of detailed route map for the selected destination to the vehicle(s) 102, on the basis of received information from the network quality adaptive map provider unit 104, is a continuous process, till the autonomous vehicle(s) 102 reaches the selected destination. Further, it is well understood that the network quality adaptive map provider unit 104 and the central map database 106 communicate with each other using cellular networks, thus when the vehicle(s) enters an area with no or limited cellular connectivity, the communication link between the central map database 106 and the network quality adaptive map provider unit 104 may break. In other words, when the vehicle(s) 102 enters an area with no or limited cellular connectivity the communication link between the central map database 106 and the vehicle(s) 102 may break which can bring the vehicle(s) 102 to halt.
[0944] To overcome these shortcomings, said system 100 further discloses having the cellular network quality layer unit 110 placed in close vicinity to the central map database 106 such that the cellular network layer unit 110 remain operatively connected to the central map database 106. In an exemplary embodiment, the cellular network quality layer unit 110 may form an integral part of the central map database 106 and thus may be placed within the central map database 106. However, the same is clear from the description and has not been depicted by any separate figure.
i00451 Further, as already discussed, the central map database 106 stores high definition digital map's of the road network for a larger geographical location. in addition, the cellular network quality layer unit 110 is configured to pre-configured with network quality and availability information of each geographical location present on the central map database 106. In another aspect, the cellular network quality layer unit 110 is further configured to constantly update said central map database 106 with network availability and quality information for each geographical location present on the central map database 106 and specifically for that of the location on the scheduled route. In order to constantly update the central map database with network quality and availability information, the cellular network quality layer unit 110 keeps on receiving network quality and availability information from network quality adaptive map provider unit 104.
[0046] In one embodiment, the network quality adaptive map provider unit 104 may be configured to receive said network quality and availability information from the vehicle(s) 102 through the backend communication unit 116 of the vehicle(s) 102. It is to be appreciated that the backend communication unit 116 is not configured with capabilities to retrieve said information along the scheduled route of the vehicle(s) thus the network quality monitoring unit 114 may he configured to perform said functionality in an embodiment, the network quality monitoring unit 114 may be configured with GPS and like technologies to retrieve signal information for each location along the scheduled route of the vehicle(s) 102. The network quality monitoring unit 11 4 may be configured to store this information locally and share the same with the cellular network quality layer unit 110 by the help of the network quality adaptive map provider unit 104, whenever a connection between the vehicle(s) 102 and the cellular network quality layer unit 110 is established.
[0047] In an exemplary embodiment, the cellular network quality layer unit 110 may use various modes to depict areas with different signal quality and strength information. In one aspect, as shown in figure 1C, the cellular network quality layer unit 110 may utilize different color coding to depict the signal strength and quality in various geographical locations present on the central map database 106. Specifically, as shown in figure IC areas coded with blue color indicate the areas with good cellular network quality and strength, green color indicates the areas with medium cellular network quality and strength and red color indicate the areas with no or limited cellular network quality and strength. It is to be appreciated the network quality and strength may be governed by various parameters such as bandwidth, stability etc. for each location present on the central map database 106.
[0048] Further in another aspect, the cellular network quality layer unit 110 may be configured to allow the network quality adaptive map provider unit 104 to query the central map database 106 about the network quality at any given point or location on the map. Additionally, the cellular network quality layer unit 110 may be configured to provide functionality to initially set or update the cellular network quality Information for any given point or location on said map.
[0049] The system 100 depicted in figure IA clearly discloses the network quality adaptive map provider unit 104 having an update unit 112. Said update unit may be configured to receive network update from the network quality monitoring unit 114 of the vehicle(s) 102 and send the same to the cellular network quality layer unit 110 to keep the central map database updates with the network quality and availability information along the scheduled route of the vehicle(s). Figure IB discloses another exemplary embodiment of system 100 where the update unit 112 forms a part of cellular network quality layer unit 112. In an exemplary embodiment, the system disclosed in figures IA and I B are identical except for the fact that the update unit 112 is placed at distant location, however the functionality of the entire system 100 remains the same.
[0050] As shown in figure 1A, the network quality adaptive map provider unit 104 is placed in close vicinity to the central map database 106 such that the network quality adaptive map provider unit 104 remain operatively connected to the central map database 106. In an exemplary embodiment, the network quality adaptive map provider unit 104 may also form an integral part of the central map database 106 and thus may be placed within the central map database 106. However, the same is clear from the description and has not been depicted by any separate figure. Said network quality adaptive map provider unit 104 is configured to select a portion of map data, using the HD route layer unit 108 to be streamed to the vehicle(s) 102 based on at least one of current position of the vehicle(s) 102, upcoming route for selected destination and the network quality on said route.
[00511 Precisely, the network quality adaptive map provider unit 104 may be configured to receive information about current position of the vehicle(s) 102, desired destination and the planned route from the current position of the vehicle(s) 102 to the desired destination from the backend communication 116 of the vehicle(s) 102. In an embodiment, the network quality adaptive map provider unit 104 may be configured to extract said information directly from AV 102 using network quality monitoring unit 114.
[0952] Based on said information, the network quality adaptive map provider unit 104 is configured to query, the central map database 106, the information about network coverage, using the corresponding map section, for the upcoming route of the AV's 102. In an exemplary embodiment, the network quality adaptive map provider unit 104 is configured to query the cellular network quality layer unit 110 about network coverage, using the corresponding map section, for the upcoming route of the AV's 102. Wherein, based on the information received, said network quality adaptive map provider unit 104 is configured to select a portion of map data to be streamed to the vehicle(s) 102. In another exemplary embodiment, the network quality adaptive map provider unit 104 is configured to select the portion of map data to be streamed to vehicle(s) 102, HD route layer unit 108, for the upcoming route of the AV's 102. It is to be appreciated that the selection of the portion of map data to be streamed to the vehicle(s) 102 may be based on at least one of current position of the vehicle(s) 102, upcoming route for selected destination and the network quality on said route.
100531 The said portion of map data is then shared, by the network quality adaptive map provider unit 104, with the of the vehicle(s) 102 to assist vehicle(s) navigate, even when the vehicle(s) passes through an area with no or limited network availability. Figure IA discloses an exemplary embodiment, in which a portion of map data depicts the selected portion (heighted by blue circle) from a route map (shown by blue bold arrow) based on at least one of current position of the vehicle(s) 102, upcoming route for selected destination and the network quality on said route.
Thus, the system 100 is configured to estimate when and how much (what portion) of the map data is to be shared with the autonomous vehicle(s) 102 to continue the movement of the autonomous vehicle(s) 102, even if the vehicle(s) 102 passes through an area with no or limited cellular network.
[0054] It is to be further appreciated that in order to make the current system operational the update unit 112, as shown in figures IA and 1B, may be configured to perpetually monitor the network quality for each geographical location through which the vehicle(s) 102 passes during scheduled route, in real-time, and share said information with the network quality adaptive map provider unit 104. Thus, in this manner the update unit 112 is configured to constantly update information about cellular network quality and strength for each location over the period of time to the cellular network quality layer unit 110. For example, in case the cellular network quality and strength of a particular location may have been week a year ago. However, if there has been any significant development in the cellular network quality and strength in that area in that particular location the sane may be updated in the cellular network quality layer unit 110.
100551 Figure 2 discloses an exemplary method 200 for continuous streaming of map data to autonomous vehicle(s) 102. The method starts at step 202 by querying, by a network quality adaptive map provider unit 104, central map database 106 with network availability and quality information for each geographical location present along the autonomous vehicle(s)s scheduled route on the central map database 106. In an exemplary embodiment, in addition to the step of querying, the method 200, is simultaneously configured to perform the steps of receiving at the central map database 106 location information and the destination information of the vehicle(s) 102. At step 204, method 200 performs the step of selecting, by a network quality adaptive map provider unit 104, a portion of map data to be streamed to the network quality adaptive map provider unit 104 based at least on one of current position of the autonomous vehicle(s), upcoming route for selected destination and network quality on said route.
[0056] In an illustrative embodiment, the step of selecting 204 may be divided into two parts. First, where the network quality adaptive map provider unit 104 may be configured to ask the HD route layer unit 108 about the route map of the corresponding areas along the scheduled route and secondly ask the cellular network quality layer unit 110 about the network quality and availability in these areas. Wherein, based on the information received, said network quality adaptive map provider unit 104 may perform the step of selecting a portion of map data to be streamed to the vehicle(s) 102.
[0057] The method further incudes sending, by the network quality adaptive map provider unit104, the portion of selected map data to the vehicle(s) 102, at step 206. The step of sending selected portion of detailed route map for the selected destination assists vehicle(s) 102 in navigating when the vehicle(s) 102 passes through an area with no or limited network. The method 200 further includes an additional step of updating, in real time, by an update unit 112, the cellular network quality layer unit 110 with network quality for each geographical location through which the vehicle(s) 102 passes during scheduled route. In an exemplary embodiment, the step of updating may be performed either from the vehicle(s) 102 or from the distant location and it completely depends on the placement of update unit 112 as illustrated in figures I A and I B. [0058] The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments. It must also be noted that as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise.
[0059] Advantages of the embodiment of the present disclosure are illustrated herein The present disclosure allows the autonomous vehicle(s) to receive the map updates from central map database even in at locations where cellular network connectivity is no or limited.
The present disclosure provides a technique to bridge network gaps between the autonomous vehicle(s) and the central map database.
The present disclosure provides smooth streaming operations between the autonomous vehicle(s) and the central map database.
J00601 Referral Numerals:
Reference Number Description
Adaptive map streaming system 102 Autonomous vehicle(s) 104 Network quality adaptive map provider unit 106 Central map database 108 HD route layer unit Cellular network quality layer unit 112 Update unit 114 Network quality monitoring unit 116 Backend communication unit Method for continuous streaming of map data 202-206 Method steps
Claims (9)
- [0061] Claims: We Claim: 1. An adaptive map streaming system for continuous streaming of map data to autonomous vehicle(s)s, said system comprising: a backend communication unit configured inside the autonomous vehicle(s); a network quality monitoring unit placed inside the autonomous vehicle(s) and operatively coupled to the backend communication unit, wherein the network quality monitoring unit is configured to perpetually monitor the network quality for each geographical location through which the vehicle(s) passes during a scheduled route; a central map database placed external to the vehicle(s) at a distant location and configured to be communicably connected to the autonomous vehicle(s), wherein the central map database comprises a high definition road map of a location, said central map database comprising: a HD road layer unit configured to provide a high definition map of the road network for the scheduled route; and a cellular network quality layer unit containing information about network quality and availability of each location on the scheduled route; and a network quality adaptive map provider unit, located outside the vehicle(s), configured to connect the central map database with the backend communication unit of the autonomous vehicle(s), wherein the network quality adaptive map provider unit is configured to query along the autonomous vehicle(s)s scheduled route the expected network coverage from the cellular network quality layer unit and the corresponding map sections from the HD road layer unit and in response predict how much new map data is to be streamed to the autonomous vehicle(s).
- 2. The system as claimed in claim 1, wherein the central map database is configured to constantly receive, from the network quality adaptive map provider unit, location information and the destination information of the autonomous vehicle(s) and in response provide the portion of detailed route map for the selected destination to assist vehicle(s) navigate, even when the autonomous vehicle(s) passes through an area with no or limited network availability.
- 3. The system as claimed in claim 1, wherein the network quality monitoring unit, placed inside the vehicle(s), is configured to share the network quality retrieved for each geographical location through which the vehicle(s) passes during the scheduled route with the cellular network quality layer unit via the network quality adaptive map provider unit.
- 4. The system as claimed in claim 1, further comprising an update unit configured to retrieve, from the network quality monitoring unit, the network quality throughout the scheduled route and share said information with the cellular network quality layer unit.
- 5. The system as claimed in claim 4, wherein the update unit is placed external to the vehicle(s) and forms a part of either the network quality adaptive map streaming unit or the cellular network quality layer unit.
- 6. The system as claimed in claim 1, wherein the central map database is configured to store high definition digital map's of the road network for a larger geographical location.
- 7. A method for continuous streaming of map data to autonomous vehicle(s)s, the method comprising; querying the central map database, the expected network coverage along the autonomous vehicle(s)s scheduled route; selecting a portion of map data to be streamed to the network quality adaptive map provider unit based at least on one of current position of the autonomous vehicle(s), upcoming route for selected destination and network quality on said route; and sending the selected portion of the map data to the autonomous vehicle(s) via the network quality adaptive map provider unit.
- 8. The method as claimed in claim 7, further comprising: receiving at the central map database location information and the destination information of the autonomous vehicle(s); and sending to the autonomous vehicle(s) via the network quality adaptive map provider unit the portion of detailed route map for the selected destination to assist the autonomous vehicle(s) in navigating even when the autonomous vehicle(s) passes through an area with no or limited network.
- 9. The method as claimed in claim 7, further comprising: updating the central map database with network availability and quality information for each geographical location present on the central map database.
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| GB2009186.4A GB2596093A (en) | 2020-06-17 | 2020-06-17 | An adaptive map streaming system for autonomous vehicle(s) and method thereof |
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| GB2009186.4A GB2596093A (en) | 2020-06-17 | 2020-06-17 | An adaptive map streaming system for autonomous vehicle(s) and method thereof |
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| GB202009186D0 GB202009186D0 (en) | 2020-07-29 |
| GB2596093A true GB2596093A (en) | 2021-12-22 |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130321424A1 (en) * | 2012-06-05 | 2013-12-05 | Seejo K. Pylappan | System And Method For Generating Signal Coverage Information From Client Metrics |
| US20150304874A1 (en) * | 2012-09-28 | 2015-10-22 | Audi Ag | Method and system for determining a mobile communications network quality and downloading mobile communications data |
| DE102017009510A1 (en) * | 2017-10-12 | 2018-03-29 | Daimler Ag | Method for updating a digital map in a vehicle |
| EP3322204A1 (en) * | 2016-11-11 | 2018-05-16 | Bayerische Motoren Werke Aktiengesellschaft | Driver assistance system and method |
| DE102017218394A1 (en) * | 2017-10-13 | 2019-04-18 | Robert Bosch Gmbh | Method and system for loading digital geographic map tiles |
| WO2020072074A1 (en) * | 2018-10-05 | 2020-04-09 | Google Llc | Improving offline map data availability |
-
2020
- 2020-06-17 GB GB2009186.4A patent/GB2596093A/en not_active Withdrawn
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130321424A1 (en) * | 2012-06-05 | 2013-12-05 | Seejo K. Pylappan | System And Method For Generating Signal Coverage Information From Client Metrics |
| US20150304874A1 (en) * | 2012-09-28 | 2015-10-22 | Audi Ag | Method and system for determining a mobile communications network quality and downloading mobile communications data |
| EP3322204A1 (en) * | 2016-11-11 | 2018-05-16 | Bayerische Motoren Werke Aktiengesellschaft | Driver assistance system and method |
| DE102017009510A1 (en) * | 2017-10-12 | 2018-03-29 | Daimler Ag | Method for updating a digital map in a vehicle |
| DE102017218394A1 (en) * | 2017-10-13 | 2019-04-18 | Robert Bosch Gmbh | Method and system for loading digital geographic map tiles |
| WO2020072074A1 (en) * | 2018-10-05 | 2020-04-09 | Google Llc | Improving offline map data availability |
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| GB202009186D0 (en) | 2020-07-29 |
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