Method and system for managing the driving of a vehicle

Abstract

The invention relates to a method for managing the driving of a vehicle, comprising: transmitting a request for map data, including road condition characteristics data and course characteristics data, corresponding to a transverse position of the road condition characteristics inside portions that subdivide a given road traffic lane laterally; and receiving and processing said data so as to control at least one controllable device of the vehicle.

Description

Description Title of the invention: Method and system vehicle traffic management

[0001] The invention relates to a method for managing the movement of a vehicle, particularly a connected vehicle. The invention also relates to a method for collecting mapping data for managing the movement of at least one vehicle in a fleet of connected vehicles. The invention further relates to a movement management system configured to implement the methods according to the invention.

[0002] In the automotive industry, it is known to use map data from databases to provide road infrastructure information to vehicle systems, such as driver assistance systems and / or electronic horizon provider modules.

[0003] Typically, this data is organized according to road segments defined longitudinally relative to the vehicle, that is, according to their proximity to the vehicle as it moves. This limits the performance of vehicle systems that use such data, for example, adaptive suspension systems, in the case of dynamic chassis adjustments while driving, or driver assistance systems, in the case of longitudinal speed management, driving recommendations, alerts, and so on. As a result, the control of such systems is limited and cannot be performed proactively in anticipation of changes in road conditions, but primarily reactively.

[0004] The invention falls within this context and aims to provide a method and system for managing the driving of at least one vehicle, thereby optimizing driving conditions. In particular, the invention advantageously enables more proactive driving, rather than simply reactive driving, in response to changes in the environment external to the vehicle. The invention also extends to a method for collecting mapping data for managing the driving of at least one vehicle in a fleet of connected vehicles.

[0005] The invention relates to a method for managing the driving of a primary vehicle equipped with a communication module and a processing module, the method being implemented within said vehicle and comprising: - the sending of a map data request to at least one remote database, via the communication module, and the return receipt of said data by the primary vehicle, the map data comprising at least one road state characteristic associated with at least one track characteristic, each track characteristic defining a transverse position of a track among at least two possible predefined tracks corresponding to distinct portions of a traffic lane of a road considered laterally subdividing said traffic lane; - the exploitation of at least part of the received mapping data, including at least one road state characteristic associated with at least one track characteristic, in order to implement the control of at least one controllable equipment of the primary vehicle based on said data. In particular, at least one trace characteristic defines a position of a trace comprising at least one road state characteristic among at least two possible predefined traces corresponding to portions of a traffic lane of a considered road subdividing transversely the traffic lane considered relative to a direction of advancement of the vehicle ego and / or relative to a direction of extension of the traffic lane considered.

[0006] Optionally, the management process also includes: - the determination, via the processing module, of the most probable route for the primary vehicle from among a plurality of possible routes between an initial location and a destination location of the primary vehicle, and the geographic filtering of at least a portion of the map data including at least one road state characteristic associated with at least one track characteristic; and / or - filtering at least one road state characteristic associated with at least one track characteristic based on at least one controllable device considered. The method according to the invention is then carried out such that at least a portion of the filtered received map data is used to control at least one controllable device of the primary vehicle.

[0007] According to a specific implementation example, the management process also includes: - the reception of geolocation data from the primary vehicle; and - the use of said geolocation data when issuing the request for map data to at least one database in order to geographically filter said data, in particular so that it includes at least map data relating to the most probable route.

[0008] Optionally, the map data provided by at least one database is structured into a plurality of layers: - the primary vehicle comprising at least one reconstruction unit configured to implement the generation of at least one organization tree of at least a portion of the received map data, said generation comprising the planarization of said received map data so as to structure it into at least one data tree relating to at least one of the at least two possible tracks and relating to at least one road state characteristic associated with said track; and - the use of received mapping data to control the operation of at least one controllable piece of equipment of the primary vehicle using at least one data organization tree.

[0009] Optionally, the received map data is organized into segments and layers, each layer relating to a type of F at least one road condition characteristic associated with at least one of the at least two tracks, each layer comprising segments representing a portion of the traffic lane of the road under consideration for which F at least one road condition characteristic under consideration has a constant or substantially constant value, each segment being delimited by two marking beacons defining the respective positions of the beginning and end of the portion of road under consideration and defining F at least one associated constant value.

[0010] According to alternative implementation examples, the reconstruction unit is configured to: - generate a single map data organization tree including all or part of the road condition characteristic map data associated with the different tracks of at least two possible tracks; or - generate a plurality of map data organization trees, each tree including all or part of the road state characteristic data associated with one of the tracks among the at least two possible tracks.

[0011] Specifically, the road state characteristic data associated with the track characteristic data relates to at least one of the following: - a level or class of adhesion, associated with at least one of the traces among the at least two possible traces, of the traffic lane in question; - a difference in adhesion between different tracks among the at least two possible tracks, corresponding to different transverse locations, of the traffic lane considered; - temporary and / or localized damage or degradation of the roadway associated with at least one of the traces among the at least two possible traces of the traffic lane in question; - a road infrastructure element, such as a speed bump or hump, associated with at least one of the at least two possible traces of the traffic lane in question; - a variation in the condition of the road resulting from external conditions, such as weather conditions, associated with at least one of the at least two possible traces of the traffic lane in question.

[0012] Optionally, the management process also includes: - the acquisition, via at least one sensor on the primary vehicle as it moves, of measured data relating to at least one road condition characteristic on a traffic lane on which the primary vehicle is traveling, said road condition characteristic being itself associated with at least one track characteristic defining at least one track comprising said road condition characteristic among the plurality of possible tracks; and - the transmission of said measured data to at least one remote database via the communication module.

[0013] Optionally, the method according to the invention may include updating at least a portion of the mapping data recorded on at least one database when the measured data transmitted differs from the mapping data recorded therein.

[0014] The invention also extends to a method for collecting mapping data for managing the driving of at least one vehicle in a fleet of connected vehicles, comprising: - the acquisition, via at least one sensor on a primary vehicle, of measured data relating to at least one road condition characteristic on a traffic lane on which said primary vehicle is traveling, said road condition characteristic being associated with at least one track characteristic, each track characteristic defining a transverse position of a track among at least two possible predefined tracks corresponding to distinct portions of a traffic lane of a road considered, laterally subdividing said traffic lane; and - the transmission of said measured data to at least one remote database via a communication module.

[0015] In particular, the data collection method according to the preceding claim further comprises: - updating at least part of the mapping data of F in at least one database when the measured data acquired and transmitted by the primary vehicle differs from pre-recorded data in said database; - the transmission of updated mapping data to at least one secondary vehicle in the vehicle fleet, and the use of said data for the control of at least one controllable piece of equipment on said secondary vehicle.

[0016] The invention also relates to a vehicle driving management system, in particular for a connected vehicle, the system comprising hardware and / or software elements implementing the management process according to the invention, the hardware elements comprising a data processing module, a communication module and a control device capable of controlling at least one controllable piece of equipment of the vehicle.

[0017] The invention also extends to a motor vehicle comprising at least one controllable equipment and a driving management system according to the invention.

[0018] The invention further extends to a computer program product comprising program code instructions stored on a computer-readable medium for implementing the steps of the rolling management process and / or the data collection process according to the invention when said program is run on a computer. Alternatively, the invention relates to a computer program product downloadable from a communication network and / or stored on a computer-readable and / or computer-executable data medium comprising instructions which, when the program is executed by the computer, cause the computer to implement the rolling management process and / or the data collection process according to the invention.

[0019] The invention finally extends to a computer-readable data recording medium on which is recorded a computer program comprising program code instructions for implementing the rolling management process and / or the data collection process according to the invention.

[0020] Further details, features and advantages will become clearer upon reading the detailed description given below, which is indicative and not exhaustive, in relation to the various implementation examples illustrated in the following figures:

[0021] Fig. 1 is a schematic view of one embodiment of a driving management system for a connected motor vehicle.

[0022] Fig. 2a is a schematic representation of an example of traces in a part of the road infrastructure.

[0023] Fig. 2b is a schematic representation of an example of traces in a part of the road infrastructure.

[0024] The [Fig.3] is a general flowchart of an example of the execution of a process for managing the driving of a connected vehicle.

[0025] Figure 4 is a flowchart of an example of the execution of a process for managing the driving of a connected vehicle, including possible execution alternatives.

[0026] Fig. 5 is a schematic view of one embodiment of a data collection system for managing the driving of at least one connected vehicle in a fleet of connected vehicles.

[0027] The [Fig.6] is a general flowchart of an example of the execution of a data collection process for the management of the driving of at least one connected vehicle of a fleet of connected vehicles.

[0028] Figure 1 schematically illustrates one embodiment of a motor vehicle. The vehicle has a thermal, electric or hybrid engine. The vehicle can also be, for example, a passenger car, a commercial vehicle, a truck, or a bus. Optionally, the vehicle can be an autonomous vehicle. Specifically, the vehicle is a connected vehicle, meaning it is equipped with a communication module, as detailed below.

[0029] Throughout the following description, the vehicle 1, which includes the means for implementing the invention, is referred to hereafter as "primary vehicle 1" or "ego vehicle" to distinguish it from other surrounding vehicles. The term "ego" does not in itself imply any technical limitation to the vehicle. "Secondary vehicles 1'" will also be identified, corresponding to vehicles of any type distinct from the ego vehicle 1 and circulating within the road infrastructure, for example, cars, bicycles, motorcycles, and others. These vehicles are also connected vehicles. A plurality of connected vehicles, including the ego vehicle 1 and at least one secondary vehicle 1', is thus defined as a "fleet" or "fleet of connected vehicles."

[0030] In the various figures representing the ego 1 vehicle, the optional components are illustrated by dotted lines. The same applies to the optional steps of the process according to the invention.

[0031] The ego 1 vehicle includes at least one controllable device 2 capable of directly or indirectly affecting the driving, in other words the vehicle's movement. For example, such a controllable device 2 is a driver assistance system 3, an autonomous driving system, a controlled suspension system 4 and / or a chassis control system, for example capable of independently controlling brakes specific to each wheel and / or controlling engine torque specific to each drive wheel.

[0032] Indeed, the 4-way electronically controlled suspension system provides dynamic suspension configured to adapt the piston pressure in real time to adjust wheel damping according to obstacles encountered or road conditions, thus enabling ride management that optimizes user comfort.

[0033] The Advanced Driving Assist System 3 (ADAS) assists a user's driving during driving phases of the ego 1 vehicle and can be controlled in various ways, for example by adapting the driving of the ego 1 vehicle itself, including its speed, by issuing alerts to the driver and / or by providing driving advice to the driver depending on the context in which the ego 1 vehicle is driving. The Advanced Driving Assist System 3 may then include a Human-Machine Interface, including a screen and / or a speaker, and / or an alert device.

[0034] Optionally, the ego 1 vehicle is equipped with a localization system 5 that allows its position to be determined within the road infrastructure, notably via satellite. This system may include, for example, a localization system for the ego 1 vehicle and / or a map of the road infrastructure. As a non-limiting example, the ego 1 vehicle's location may be provided by a GPS (Global Positioning System). The ego 1 vehicle's localization system allows, for example, the extraction of information from at least one map database concerning road infrastructure, speed limits, topology, and / or road geography in the vicinity of the vehicle. The localization system 5 preferably includes an inertial measurement unit (IMU), also known as an Automotive Dynamic Motion Analyzer (ADMA).

[0035] Optionally, the ego vehicle 1 and / or the driver assistance system 3 includes an electronic horizon provider module, comprising the location means 5 or configured to communicate with the location means 5 fitted in the ego vehicle 1 in order to provide an electronic horizon, also referred to as an e-horizon. In a known, though not detailed, manner, the electronic horizon is an estimated map of the road infrastructure and the environment outside the vehicle. In particular, the electronic horizon includes a set of possible roads or routes located ahead of the ego vehicle, specifically over a defined distance, for example, on the order of 5 to 10 km, and characteristic targets that may relate to any element defining the road infrastructure in such an area, as further detailed below.

[0036] Alternatively, the ego 1 vehicle may include at least one sensor 6, or a plurality of sensors 6, capable of extracting information relating to the environment outside the vehicle and / or relating to the vehicle itself. For example, such a sensor 6 could be a detection device such as a camera. Alternatively, such a sensor 6 could be mounted on the chassis and / or a wheel of the ego 1 vehicle, such as an ABS sensor and / or an external temperature sensor 6. In another example, said sensor 6 could be mounted on a windshield wiper blade and be capable of detecting inclement weather.

[0037] Specifically, the driver assistance system 3 is configured to receive information and data from at least one sensor 6 and / or the electronic horizon provider module fitted to the vehicle. Alternatively or additionally, the driver assistance system 3 takes into account information provided by the location means 5.

[0038] The vehicle according to the invention further comprises a vehicle driving management system 10, illustrated in [Fig. 1], including hardware and / or software components capable of implementing a driving management method 100 for at least one vehicle as described below. These hardware components include at least one data processing module 7, a communication module 8, and a control device 11 capable of controlling at least one controllable vehicle component 2 from among those mentioned above.

[0039] The communication module 8 enables the ego 1 vehicle to receive and / or transmit data. For example, the communication module 8 is configured to receive map data from at least one remote B1 database via a low-frequency or high-frequency wireless link. This could, for example, be a wireless link based on cellular, Wi-Fi, or Bluetooth technologies. Preferably, such a B1 database is located on a remote server. Alternatively, and not detailed, such a database is located in a secondary vehicle 1'. The communication module 8 allows, in particular, the extraction of map data relating to road infrastructure. Conversely, the communication module 8 is capable of transmitting data to at least one remote database or other database according to the same principles.

[0040] The processing module 7 is capable of receiving data from at least one driver assistance system 3, the location means 5, at least one sensor 6, and / or the communication module 8. It includes at least one computer with hardware and software resources, specifically at least one processor or microprocessor, capable of processing said data and executing instructions for the implementation of a computer program. The processing module 7 includes, or cooperates with, memory elements of the vehicle ego 1. In one particular, optional embodiment, the processing module 7 includes at least one driver assistance system 3, the location means 5, and / or the electronic horizon provider module.

[0041] Optionally, the processing module 7 includes a reconstruction unit 9 configured to organize the received map data into at least one tree containing at least a portion of said data. Specifically, it allows the data, initially organized into multiple layers, to be consolidated into a single layer. In other words, the reconstruction unit 9 is capable of planarizing at least a portion of the received data. The reconstruction unit 9 is capable of generating at least one data tree as new map data is received and / or as the ego 1 vehicle moves. It is also capable of removing portions, or branches, of the data tree that are not relevant or are no longer relevant, for example, because they are temporally and / or geographically outdated due to the movement of the ego 1 vehicle.

[0042] Note that, optionally, management system 10 may include at least one of the following: - the means of localization 5; - one or more sensors 6; - a user alerting device and / or a Human-Machine Interface comprising at least one screen and / or a speaker capable of communicating information to a user.

[0043] Optionally, the ego 1 vehicle according to the invention further comprises a data collection system 10', illustrated in [Fig. 5], including hardware and / or software components capable of implementing a method for collecting mapping data 200 for managing the driving of at least one vehicle in a fleet of connected vehicles, as described below. These hardware components include at least one data processing module 7, a sensor 6, and a communication module 8, as described above. In particular, the data collection system 10' may be included within the management system 10 according to the invention.

[0044] An execution method of the vehicle ego 1 driving management process 100 is described below with reference to [Fig.3] or 4. Such a method is also comparable to a vehicle ego 1 operating method according to the invention equipped with a management system 10 as described above.

[0045] In general, management process 100 includes the transmission E01 of a map data request to at least one remote mapping database B1. Such a request is implemented via the communications module 8, for example, based on an instruction issued by the processing module 7.

[0046] Typically, maps are described in various computer file formats, such as GPX (GPS Exchange Format), KML (Keyhole Markup Language), or others. For example, in GPX format, routes are represented by an ordered list of markers, each representing, for instance, the location of road infrastructure features, such as curves, intersections, or other points of interest leading to a destination. Optionally, these markers include geolocation data, such as longitude and latitude, and data relating to the physical characteristics of the road infrastructure.

[0047] In specific examples, map data is segmented, meaning it defines segments of a road or traffic lane delimited by markers, corresponding to points of interest or passage, including geolocation marking the beginning and end of the segment. It should be noted that map data may include intermediate markers placed along a segment between the markers that define its boundaries. Each marker indicates a change in at least one characteristic of the road or traffic lane, that is, a point change, such as the presence of an obstacle, or a change starting from the marker, such as a change in speed limit. Here, "segment" refers to a portion of a whole; a segment can represent straight, curved, or other sections of a traffic lane or road.Also, a traffic lane or road comprises a plurality of successive segments, that is to say, arranged one after the other longitudinally relative to the vehicle ego.

[0048] For example, the maps considered are SD maps for "Standard Definition," or "SD Maps" in English, or HD maps for "High Definition," or "HD Maps" in English. Note that, optionally but preferably, the map data is organized into multiple layers, each layer corresponding to a type of map data, for example, at least one type of road condition characteristic data as detailed below.

[0049] In particular, according to the invention, the required mapping data includes data relating to at least one road state characteristic, in particular to a plurality of road state characteristics, corresponding to physical characteristics of a traffic lane of a road travelled by the vehicle ego 1, F at least one road state characteristic being associated with at least one track characteristic, defining a transverse position of a track comprising F at least one road state characteristic considered from among at least two possible predefined tracks corresponding to portions of a traffic lane of a road considered, in particular lateral portions or portions laterally subdividing said lane.In other words, these at least two possible tracks subdivide, transversely or laterally, a traffic lane of a given road, relative to a direction of travel of the vehicle in question (here, for example, vehicle ego 1), and / or relative to a direction of extension of the traffic lane of the given road. Thus, the track characteristic defines which track, among a plurality of predefined possible tracks virtually subdividing a traffic lane of a given road, includes at least one road state characteristic to which it is associated.

[0050] In other words, the data relating to at least one track feature associated with at least one road condition feature corresponds to an indication of the location of said road condition feature within a considered traffic lane of a travelled road, among the at least two tracks virtually subdividing said lane. Thus, each considered traffic lane of a road in the road infrastructure comprises a plurality of tracks allowing said traffic lane to be subdivided along a direction transverse, or even orthogonal, to a direction of advancement of the vehicle ego 1 in the road infrastructure and / or to a direction of extension of the traffic lane of the road in question; that is to say, here, subdividing each traffic lane along a transverse direction orthogonal to the longitudinal direction.The track characteristic thus allows us to define the location of a characteristic relative to several possible tracks included in one side of a given traffic lane, or comprising one side of a given traffic lane. Specifically, the data relating to the track characteristic relates to at least one possible track among at least two tracks of a traffic lane on a given road within the road infrastructure. The presence of a given road condition characteristic at the level of one of the possible tracks, and the absence of track characteristic data concerning at least one other possible track among the at least two tracks subdividing the traffic lane, allows, for example, the implicit definition of an absence of road condition characteristics at the level of at least one other possible track.

[0051] According to an example of implementation, illustrated in [Fig. 2a], the tracks considered correspond to at least two strips extending over a portion of the width of a traffic lane of a given road. Specifically, a first strip T1, or right strip, corresponds to the trajectory of the right front and rear wheels of a vehicle with at least four wheels, while a second strip T2, or left strip, corresponds to the trajectory of the left front and rear wheels of the same vehicle. The widths of the tracks considered may then exceed average tire dimensions and / or be defined based on a predefined average spacing. In particular, the different tracks are of equal or nearly equal dimensions, especially width.In such an example, trace characteristic data relating to a central area are not provided, as these are less, or even of little, relevance and are typically only required in the event of an overshoot or other more exceptional situation.

[0052] According to an alternative or additional embodiment, the plurality of tracks corresponds to adjacent subdivisions of the traffic lane of the road under consideration, defined along the transverse, or even orthogonal, direction to the direction of travel of the vehicle ego 1 and / or the direction of extension of the traffic lane under consideration. In particular, the different tracks are of equal or substantially equal dimensions, especially width. The traffic lane then comprises at least two tracks positioned more or less to the left within the traffic lane of the road under consideration. For example, as illustrated in [Fig. 2b], when the traffic lane is divided into two tracks T1', T2', these are adjacent and in contact with each other, one comprising the left side of the traffic lane and the other comprising its right side.

[0053] It is understood that trace characteristic data can be defined in relation to more than two traces, the number of traces corresponding to the number of transverse bands or subdivisions of the traffic lane under consideration.

[0054] Track characteristic data thus provides more precise information regarding the road condition characteristics of road infrastructure. This allows for more refined control of the vehicle's equipment and proactive vehicle control, rather than the reactive control characteristic of prior art vehicles. Furthermore, track characteristic mapping data can be advantageously useful for various vehicle types, including two-wheeled vehicles, which typically travel further to the right of a given lane or further to the left when overtaking. Track characteristic data is provided for at least one of the at least two possible tracks, that is, for all or some of the tracks within the defined plurality of tracks.Furthermore, track characteristic data is defined for each traffic lane of a given road. In one implementation example, the track characteristic data is organized in a specific layer of map data. Alternatively, track characteristic data and road condition characteristic data are combined and distributed across different map data layers, each layer being specific to a particular type of road condition characteristic data.

[0055] Road condition data, also known as "road state" data, refers to data defining the physical characteristics of at least one traffic lane, specifically the lane traveled by the vehicle ego, on a given road. This data is associated with track characteristic data to define its location relative to at least one of the predefined possible tracks as described above.For example, road condition characteristic data relates to at least one of the following: - a level or class of grip associated with at least one of the at least two possible traces, i.e. at least one transverse portion of the traffic lane of the road in question, referred to in English as "grip", the level of grip being able to be defined relative to a grip scale, for example from 0 to 1, or according to classically defined classes, for example of the type "rough", "smooth", "semi-smooth" or other, or even classes of grip values; - a difference in adhesion between distinct traces of the traffic lane of the road in question, corresponding to different transverse locations of the traffic lane in question, for example a difference in adhesion between the right trace and the left trace of said traffic lane, also called a "grip split" and / or between longitudinally successive portions of the traffic lane of the road in question; - temporary and / or localized damage or degradation of the roadway, such as a pothole, oil spill, sand or other, and the characteristics associated with it, for example all or part of its dimensions, its severity or other, associated with at least one of the traces among the at least two possible traces of the traffic lane in question; - a road infrastructure element, such as a speed bump, speed hump or other, as well as the characteristics associated with it, for example its slope, its dimensions, the presence of asymmetry or other, associated with at least one of the traces among the at least two possible traces of the traffic lane in question; - a variation in the condition of the road resulting from external conditions, such as weather conditions, for example an accumulation of water likely to generate aquaplaning situations, ice patches or other, all of which is associated with at least one of the traces among the at least two possible traces of the traffic lane in question.

[0056] Such road condition characteristic data, thus associated with the less a trace characteristic allows to define with more precision the road infrastructure compared to previous art defining only the road infrastructure according to portions, or segments, succeeding longitudinally relative to the vehicle ego 1, that is to say portions of traffic lane succeeding each other as the vehicle ego 1 advances.

[0057] The invention thus makes it possible, for example, to define friction data for right and / or left sections of a traffic lane segment of a given road. In this way, for homogeneous friction values—that is, equal or nearly equal values—over significant distances, it is not necessary to store as much data. The same applies to a difference in friction.

[0058] Thus, for example, a pothole will be marked in the map data by a tag comprising at least one trace characteristic attribute indicating its position to the right or left of the traffic lane and at least one attribute defining its characteristics, such as its size, severity, or other features, particularly based on predefined scales. Similarly, a change in the traffic lane's grip will be marked by a tag delimiting a new segment or an intermediate tag indicating a change in grip value, or grip class, at at least one of the predefined tracks or at the various possible track locations.As yet another, non-limiting example, a speed bump may be marked with at least two tags, one at the entrance and one at the exit, comprising track location attributes and characteristics, such as height, slope, or other features, associated with at least one of the tracks. For example, for a given speed bump, a first entrance tag may include data associated with one of the possible tracks, while a second entrance tag may include distinct data associated with a specific track among the at least two possible tracks. It is understood that the same applies to at least one exit tag for such a speed bump.

[0059] The management process 100 then includes the return receipt E02 of such mapping data by the ego 1 vehicle, via the communication module 8. As described above, the received mapping data is optionally organized in a segmented manner, each segment representing a portion of the roadway of a traffic lane specific to a possible route for which the various data are constant. As indicated above, each segment is delimited by two markers representing the variation of a data type. It should be noted that, optionally, a segment may include at least one intermediate marker, placed along the length of the segment between the delimiting markers; such a marker also representing a variation in at least one type of acquired data.

[0060] The sending and receiving of map data requests (E01) can occur while the vehicle is in motion, i.e., as it moves along the road infrastructure. The processing module 7, for example, at least one driver assistance system 3 and / or the electronic horizon provider module, then requests the necessary map data. The sending of such an E01 request, and consequently the receiving E02 of map data, can be executed in real time or at regular time intervals.

[0061] The method according to the invention further comprises the processing E04, by the processing module 7, of the mapping data, that is to say, the associated road condition and track characteristic data, in order to implement the control, or piloting, of the operation of at least one of the vehicle's controllable equipment 2. In particular, as described above, at least one piece of equipment capable of being piloted from the acquired mapping data is selected from among the electronically controlled suspension system 4, the chassis control system, at least one driver assistance system 3, and / or an autonomous driving system. The control device 11 is thus capable of transmitting piloting commands, or instructions, to at least one of the controllable equipment 2.

[0062] For example, in the case of the adaptive suspension system 4, mapping information relating to different track locations and road condition characteristics, including grip, surface type, the presence of specific road infrastructure elements, or localized incidents, allows for optimized anticipation of various upcoming events on the most probable route, particularly based on their proximity to the vehicle ego 1, and thus for adapting the stiffness of the vehicle's left and right suspensions according to the variations associated with different track locations. A similar principle applies, mutatis mutandis, to the chassis control system.

[0063] At least one driver assistance system 3 or the autonomous driving system can similarly use map data to predict the avoidance of detected incidents or to adapt the vehicle's driving, for example its speed or lateral trajectory, in an optimized manner. For example, when avoiding a pothole, data relating to the track characteristic combined with road condition characteristics allows for a more precise location of such an incident and thus optimizes the driving adjustments of the implemented ego 1 vehicle. The same applies to driving recommendations or advice implemented via the driver assistance system 3, particularly through the human-machine interface and audible and / or visual alerts that can be adapted by the control system to clarify the track characteristic information associated with an upcoming event.

[0064] It is understood that such examples are in no way limiting and that the invention extends to other examples of exploitation of acquired cartographic data.

[0065] Optionally, the vehicle ego management process 100 further includes the determination E031 of a most probable path from among a plurality of possible routes between an initial location, corresponding to a position of the vehicle ego 1 in the road infrastructure at time t, and a destination location, corresponding to a potential position of the vehicle ego 1 in the road infrastructure at time t+x. The determination E031 of a most probable path is implemented using known, but not detailed, means and methods. The determination E031 of a most probable path is implemented by the processing module 7, in particular via at least one driver assistance system 3 and / or the electronic horizon provider module.

[0066] According to embodiment examples, the most probable route is determined from map data relating to the road infrastructure, for example obtained during a previous implementation of the management method according to the invention, and the position of the ego vehicle. Optionally, such data also includes statistical data on the traffic volume of the various roads in the road infrastructure. Additionally or alternatively, the most probable route is defined from historical data of routes traveled by the ego vehicle 1 in the past, whether or not entered by the user in the location means 5. Alternatively, the most probable route is a route entered by the user for the current journey, for example in the location means 5, via a device connected to the ego vehicle or otherwise.

[0067] Optionally, the E01 map data request is generated based on the most probable route, ensuring that the data includes at least some information relevant to that route—specifically, the portion of the road infrastructure that the ego 1 vehicle is most likely to travel in the coming moments. This E01 request, and consequently the E02 map data reception, can be executed in real time or at regular intervals. The determination of the most probable route and the map data request associated with it are thus updated as the vehicle moves, with the initial location used to determine the route being updated and adjusted accordingly.These steps are thus repeated with the movement of the vehicle, the process according to the invention thus being able to include several iterations of the determination of the most probable route E031 for at least one iteration of the emission of a request E01 of data associated with said route.

[0068] Optionally, the method according to the invention further includes at least one filtering step E032 of at least a portion of the map data. Such filtering is implemented, for example, by the processing module 7, for example, by at least one driver assistance system 3 and / or the electronic horizon provider module. Such filtering may be performed prior to the transmission of the map data request E01, with the processing module 7 issuing a filtering instruction to the communication module 8 so as to receive filtered map data relevant to the vehicle ego 1, and / or such filtering may be performed after the map data is received E02 by the processing module 7.

[0069] In an example implementation, such filtering is geographic filtering, configured to extract only a portion of the map data related to the most probable route and roads geographically close to it. Geographic filtering refers to filtering based on geographic data; in this case, filtering to retain only data relating to road segments located on the most probable route.

[0070] Additionally, such filtering is performed based on the type of map data, particularly road condition characteristic data. The selected map data is defined by the fact that at least one controllable device (F) is capable of using it. This principle advantageously reduces the amount of data acquired.

[0071] For example, when only the adaptive suspension system 4 uses the map data acquired within the vehicle, road condition data relating to grip are relevant, while data relating to speed limits are not. It should be noted, as explained further below, that the filtering performed during the E02 acquisition of the map data is then contingent upon the various equipment likely to use it, and that further sorting or filtering of said data may subsequently be implemented, as explained further below.

[0072] According to a preferred example of process execution, the electronic horizon provider module, here included in the processing module 7, is configured to determine the most probable route, request map data via the communication module 8 and use said data. In particular, the electronic horizon provider module is configured to request geographically relevant map data as the ego 1 vehicle moves forward, particularly on the basis of a most probable route among a plurality of possible routes, as described above.

[0073] According to one example of implementation, the electronic horizon provider module receives extracts, or portions, of defined surface maps, which can be likened to "tiles", for example corresponding to a 1km x 1km map portion, depending on the movement of the ego 1 vehicle in the road infrastructure.

[0074] The electronic horizon provider module is thus capable of determining, directly or indirectly, the initial location of the ego 1 vehicle and therefore an initial "tile," or starting tile, containing that location. As the vehicle moves, the electronic horizon provider module can calculate the most probable route and, as needed, requests a map data tile containing the portion of the most probable route ahead. Similarly, as described above, the electronic horizon provider module optionally performs filtering of the acquired map data.As indicated above, such filtering can be a geographical filtering of the map data, so that, among the map data associated with a given "tile", only the data relating to the most probable route and at least part of the neighboring roads, for example connected to it, are extracted and / or a filtering by type of data of the map data of the given tile, depending on the equipment to be piloted 2 of the vehicle ego 1.

[0075] It is understood that such a principle applies mutatis mutandis to a processing module 7 of the type driver assistance system 3 instead of the electronic horizon provider module.

[0076] Optionally, the map data may also include vehicle geolocation data. The management method 100 according to the invention may then include using said geolocation data when issuing the map data request E01 to at least one database B1 in order to geographically filter said data so that, for example, it includes at least map data relating to the most probable route.

[0077] Optionally, the management method 100 according to the invention further comprises the generation E033, via the reconstruction unit 9 of the processing module 7, of at least one organizational tree of at least a portion of the received map data relating to at least one of the at least two possible tracks and relating to the associated road condition characteristic data. In particular, such generation E033 enables the planarization of said received map data, when it is initially organized into a plurality of layers so as to structure it into at least one data tree. For example, and without limitation, at least one considered data tree represents the most probable route and the associated road condition and track characteristics.

[0078] The exploitation step E04 described above can then be executed so as to take into account at least one data organization tree thus generated instead of the map data received in its raw state, or optionally filtered.

[0079] In the at least one tree thus generated, each branch, or node, represents a marker or segment of the most probable route. The different branches of the tree originating from the different branches represent changes in the characteristics of the road infrastructure included in the most probable route, allowing for the anticipation of potential changes in the characteristics of the most probable route. This principle enables proactive traffic management, particularly when the processing module 7 performs the calculations necessary to determine the most probable route and / or when the reconstruction unit 9 adjusts an existing data tree or generates a new one.Thus, the E033 generation of the most probable route reconstruction tree is executed in a segmented manner, with each generated branch corresponding to a portion of the most probable route for which the various data are constant. The branches correspond, for example, to a variation in the type of map data received or to a change of lane or road, for example at an intersection.

[0080] Note that the base, or root, of the tree in question corresponds to the initial location of the ego 1 vehicle, for example, a segment of the map, on which the ego 1 vehicle is located at a given moment. Therefore, such a tree and its base evolve with the movement of the ego 1 vehicle, and in particular its evolution along different segments as described above.

[0081] The at least one tree thus generated includes information provided by the acquired map data, covering at least road condition and track characteristics. Optionally, this tree also takes into account at least one source location, or geolocation, of the ego 1 vehicle at the time of the initial generation of said tree. For example, the root of the tree does not directly include geolocation data. In particular, the ego 1 vehicle is able to identify on which "branch" of the tree in question it is moving when the vehicle starts and continues moving. For example, such identification can be performed via geolocation data provided by the driver assistance system 3, the electronic horizon provider module, and / or other sources.Geolocation data is therefore not directly required by the reconstruction unit 9 when generating at least one tree.

[0082] Specifically, the tree is configured to include distances separating considered branches from the vehicle ego 1, i.e., separating changes, and / or distances separating a future event from the beginning of a given branch. In other words, such a tree allows, among other things, the definition of a longitudinal distance separating an initial location, a branch, and / or the vehicle ego 1 from at least one considered road state characteristic associated with at least one track characteristic.

[0083] Specifically, the generated tree does not necessarily include the geographical positions, or geolocations, of the various road condition characteristics of a given road, for example, but not limited to, the most probable route. Instead, it includes distances separating, within each branch, an event from the beginning of that branch. Such distances can be determined by the ego 1 vehicle, for example, by the processing module 7. As the ego 1 vehicle moves, and by extension its virtual movement along at least one tree, the ego 1 vehicle is thus able to know its position within a given branch and the distance separating it from the next event among the road condition characteristics mentioned above. The reconstruction device 9 is thus able to know: - if the vehicle ego 1 moves outside of a given branch, particularly in such a way as to cause the root of the given tree to evolve; and / or - if map data, in particular a segment of map data, is included in the most probable route, for example so as to update the tree under consideration and / or implement a new calculation of the most probable route when the vehicle ego 1 leaves said route.

[0084] The E033 generation of F, with at least one tree, allows for the organization of acquired road condition characteristic map data according to their proximity to the ego 1 vehicle, for example, within the most probable route. It also determines whether this data is associated with one of the possible tracks or if it is common to the different possible tracks, in addition to the data typically provided by the map. Such generalization can advantageously allow for data planarization so that the data is contained within a single data layer, in this case, a tree. This enables a more precise description of the road infrastructure, and therefore more accurate and efficient management of the ego 1 vehicle's journey, without requiring major modifications to the ego 1 vehicle's equipment.

[0085] It should also be noted that the reconstruction unit 9 is capable of generating a plurality of trees in parallel.

[0086] In an example execution, the processing module 7, specifically the reconstruction unit 9 it includes, is configured to generate a tree containing route state characteristic data for each of the at least two possible traces. In other words, the reconstruction unit 9 generates multiple data trees in parallel, each containing route state characteristic and trace characteristic data for one of the at least two possible traces.

[0087] According to an alternative, preferred execution example, the reconstruction unit 9 is configured to generate a single data organization tree comprising road state characteristic data associated with the various possible traces of the plurality of traces. In such an alternative, data variations related to a change in a given trace or a change in the location of a road state characteristic from one trace to another can then be marked with a branch and a new branch.

[0088] Optionally, the reconstruction unit 9 can be configured to filter the received mapping data to identify relevant data for at least one controlled device 2. In other words, the reconstruction unit 9 can sort the data by type as described above, extracting and using only the data relevant to a predefined controlled device 2.

[0089] Specifically, the reconstruction unit 9 is associated with at least one of the aforementioned controllable devices 2. Preferably, the ego vehicle 1 can include both reconstruction units 9 and controllable devices 2, each reconstruction unit 9 being associated with a controllable device 2 and configured to generate at least one data tree as described above, notably from filtered map data types relevant to said controllable device 2.

[0090] Optionally, the method for managing the driving of the ego 1 vehicle 100 further includes the acquisition E05 by the ego 1 vehicle of measured driving data relating to at least road condition characteristics and track characteristics as described above, such measured data being acquired during the movement of the ego 1 vehicle within the road infrastructure by means of at least one sensor 6 so as to detect road condition characteristics present in front of the ego 1 vehicle and the associated track characteristics, defining F at least one track comprising a road condition characteristic considered from among the at least two possible tracks. Such acquisition E05 is carried out in real time or at regular time intervals in parallel with at least some of the steps of the method according to the invention described above and relates to at least one lane of a road traveled by the ego 1 vehicle.The data considered is thus acquired directly by the ego 1 vehicle, for example by means of a camera or a sensor 6 fitted on the chassis or at the level of a wheel, as described above.

[0091] The method according to the invention can then advantageously include the transmission E06 of the measured driving data thus acquired directly by the vehicle ego 1 to at least one database Bl. Such a transmission is then implemented via the communication module 8. Alternatively, such a transmission can be carried out via a device connected to the vehicle, such as a telephone.

[0092] Optionally, the vehicle 100 ride management method according to the invention further includes updating E07 at least part of the map data recorded on at least one database Bl when the measured ride data acquired by the vehicle ego 1 differs from the recorded map data.

[0093] The E07 update step also includes a substep for comparing measured driving data acquired via at least one sensor 6 with recorded map data. The latter is updated when it differs from the acquired measured driving data. Optionally, but preferably, the E07 update of the recorded map data is conditional. For example, the E07 update step is implemented when a number of connected vehicles in the connected vehicle fleet exceeding a predefined threshold transmits similar or substantially similar measured driving data for a defined location and time period.

[0094] It is understood that, in such an embodiment, the secondary vehicles 1' capable of transmitting data then include equipment similar to that described with reference to the ego 1 vehicle and are capable of performing at least part of the management process 100 according to the invention, namely in particular at least the acquisition E05 of measured driving data via at least one sensor 6 and the transmission E06 of such data as described above.

[0095] The ego 1 vehicle is thus able to participate in the regular feeding of mapping databases so as to allow the updating of mapping data by providing measured driving data and so as to strengthen the reliability of data initially transmitted by secondary connected vehicles circulating in the road infrastructure.

[0096] The invention also extends to a method for collecting 200 mapping data for managing the driving of at least one vehicle in a fleet of connected vehicles, illustrated in [Fig. 6], comprising the acquisition E10 of measured driving data relating to road condition characteristics associated with at least one track characteristic by at least one connected vehicle equipped with a communication module 8, in particular equipped with a collection system 10' as described above, via at least one sensor 6. Note that such data acquisition E10 can be implemented by the ego vehicle 1 or any secondary connected vehicle 1' equipped with at least one communication module 8 and at least one sensor 6.

[0097] The road condition characteristic data here corresponds to all or part of the examples listed previously.

[0098] Such data is acquired via one or more sensors 6 associated with at least one wheel and / or the chassis of the vehicle in question, such as an ABS sensor, a camera, wheel alignment sensors, an inertial measurement unit, or other similar devices. Optionally, such data is processed by the processing module 7, for example, to associate it with a predefined class.

[0099] These same sensors 6 are also configured to acquire data relating to the trace characteristic associated with said road condition characteristics, thus allowing to define with greater precision the position of the different physical characteristics of the road infrastructure by specifying the lateral, or transverse, position of said characteristics, in relation to the previous art defining only the road infrastructure according to portions, or segments, succeeding each other longitudinally relative to the ego vehicle, that is to say portions of traffic lanes succeeding each other as the ego vehicle advances.

[0100] The method of collecting 200 mapping data for the management of the driving of at least one vehicle in a fleet of connected vehicles includes, subsequently, the transmission El 1 of the measured driving data thus acquired to at least one database B1 via the communication module 8.

[0101] Optionally, the data collection method 200 further includes updating map data recorded in at least one database B1 when the measured driving data transmitted by at least one connected vehicle differs from the map data recorded in the database B1. Optionally, such an update is conditional, with the description above referring to update step E07 then applying mutatis mutandis.

[0102] Optionally, the data collection process 200 includes the transmission E12 of at least some of the updated map data to at least one vehicle in the connected vehicle fleet and the use E14 of said data, including road condition and track characteristic data, for monitoring the operation of at least one controllable device in said vehicle. The preceding description relating to the map data use step E04 then applies mutatis mutandis. In particular, the data collection process 200 may include all or part of the steps of determining E031 a most probable route, issuing a request E01 for map data, generating E033 at least one data tree and / or using E04 said data as described above, the above description applying mutatis mutandis.

[0103] The method and system according to the invention thus advantageously optimize the proactive control of vehicle equipment by enabling the use of more precise mapping data. The present invention also extends to optimizing mapping data by allowing its collection and updating in an optimized and dynamic manner as connected vehicles pass by. The invention thus advantageously optimizes the management of a fleet of connected vehicles. Furthermore, the proposed solution is low-cost and easily implemented on existing vehicles.

[0104] The present invention is not limited to the means and configurations described and illustrated herein, and also extends to any equivalent means or configuration and to any technically operative combination of such means insofar as they ultimately fulfill the functionalities described and illustrated in this document.

Claims

Demands

1. Method for managing the rolling (100) of a primary vehicle (1) equipped with a communication module (8) and a processing module (7), the process being implemented within said vehicle and comprising: - the transmission (E01) of a map data request to at least one remote database (Bl), via the communication module (8), and the reception (E02) in return of said data by the primary vehicle (1), the cartographic data comprising at least one road state characteristic associated with at least one track characteristic, each track characteristic defining a transverse position of a track among at least two possible predefined tracks corresponding to distinct portions of a traffic lane of a road considered laterally subdividing said traffic lane; - the exploitation (E04) of at least part of the received mapping data, including at least one road state characteristic associated with at least one track characteristic, in order to implement the control of at least one controllable equipment (2) of the primary vehicle (1) according to said data.

2. Management method (100) according to the preceding claim, including, in addition: - the determination (E01), via the processing module (7), of the most probable route of the primary vehicle (1) from among a plurality of possible routes between an initial location and a destination location of the primary vehicle (1), and the geographic filtering of at least a portion of the map data comprising at least one road state characteristic associated with at least one track characteristic; and / or - filtering of at least one route state characteristic associated with at least one trace characteristic, according to at least one controllable equipment (2) considered; at least part of the filtered received map data being used to control at least one controllable piece of equipment (2) of the primary vehicle (1).

3. A management method (100) according to any one of the preceding claims, wherein the map data provided by F in at least one database (B1) are structured into a plurality of layers: - the primary vehicle (1) comprising at least one reconstruction unit (9) configured to implement the generation (E033) of at least one organization tree of at least a portion of the received map data, said generation (E033) comprising the planarization of said received map data so as to structure them into at least one data tree relating to at least one of the at least two possible tracks and relating to at least one road state characteristic associated with said track; and - the exploitation (E04) of received map data to control the operation of at least one controllable equipment (2) of the primary vehicle (1) using the at least one data organization tree.

4. A management method (100) according to the preceding claim, wherein the rebuilding unit (9) is configured to: - generate a single map data organization tree including all or part of the road condition characteristic map data associated with the different tracks of at least two possible tracks; or - generate a plurality of map data organization trees, each tree including all or part of the road state characteristic data associated with one of the tracks among the at least two possible tracks.

5. A management method (100) according to any one of the preceding claims, wherein the route state characteristic data associated with the track characteristic data relate to at least one of: - a level or class of adhesion, associated with at least one of the traces among the at least two possible traces, of the traffic lane in question; - a difference in adhesion between different tracks among the at least two possible tracks, corresponding to different transverse locations, of the traffic lane considered; - temporary and / or localized damage or degradation of the roadway associated with at least one of the at least two possible marks of the traffic lane in question; - a road infrastructure element, such as a speed bump or hump, associated with at least one of the at least two possible marks of the traffic lane in question; - a variation in the condition of the road resulting from external conditions, such as weather conditions, associated with at least one of the at least two possible traces of the traffic lane in question.

6. A management method (100) according to any one of the preceding claims, further comprising: - the acquisition (E05), via at least one sensor (6) of the primary vehicle (1) as it moves, of measured data relating to at least one road condition characteristic on a traffic lane on which the primary vehicle (1) is traveling, said road condition characteristic being itself associated with at least one track characteristic defining at least one track comprising said road condition characteristic among the plurality of possible tracks; and - the transmission (E06) of said measured data to at least one remote database (Bl), via the communication module (8).

7. Method for collecting (200) mapping data for managing the movement of at least one vehicle in a fleet of connected vehicles, comprising: - the acquisition (E10), via at least one sensor (6) of a primary vehicle (1), of measured data relating to at least one road condition characteristic on a traffic lane on which said primary vehicle (1) is traveling, said road condition characteristic being associated with at least one track characteristic, each track characteristic defining a transverse position of a track among at least two possible predefined tracks corresponding to distinct portions of a traffic lane of a road considered laterally subdividing said traffic lane; - the transmission (El 1) of said measured data to at least one remote database (Bl) via a communication module (8).

8. A method for collecting (200) data according to the preceding claim, further comprising: - updating (E12) at least a portion of the mapping data from at least one database (B1) when the measured data acquired and transmitted by the primary vehicle (1) differs from pre-recorded data in said database (B1); and - the transmission (E13) of updated mapping data to at least one secondary vehicle (1') of the vehicle fleet, and the use (E14) of said data for the control of the operation of at least one controllable equipment (2) of said secondary vehicle (1').

9. Vehicle management system (10), in particular a connected vehicle, the system comprising hardware and / or software elements implementing the management method according to any one of claims 1 to 6, the hardware elements comprising a data processing module (7), a communication module (8) and a control device (11) capable of controlling at least one controllable vehicle equipment.

10. Motor vehicle comprising at least one controllable equipment (2) and a driving management system (10) according to the preceding claim.

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