Method and device for determining the autonomy level of a second vehicle by a first vehicle

Abstract

The present invention relates to a method and device for determining the autonomy level of a second vehicle (12) traveling in the vicinity of a first vehicle (11). To this end, representative data of the second vehicle (12) are obtained by the first vehicle (11) from at least one device onboard the first vehicle (11). The data is acquired by an onboard camera of the first vehicle (11) and / or received from the second vehicle (12) via a wireless connection. At least two pieces of information representative of the second vehicle (12) are determined by processing the data obtained. The autonomy level of the second vehicle (12) and a confidence index associated with the autonomy level are determined from these at least two pieces of information. Figure 1 (for the abstract)

Description

Title of the invention: Method and device for determining a level of autonomy of a second vehicle by a first vehicle Technical field

[0001] The present invention relates to methods and devices for determining a level of autonomy of a second vehicle traveling in an environment of a first vehicle, in particular a motor vehicle. The present invention also relates to a method and a device for controlling the first vehicle as a function of the level of autonomy of the second vehicle. Technological background

[0002] Certain contemporary vehicles are configured to travel in a so-called autonomous or semi-autonomous mode, that is to say under the supervision of a set of functions or system(s) or driving assistance, called AD AS (from the English "Advanced Driver-Assistance System" or in French "Advanced Driving Assistance System") on board which ensure under certain conditions the control of the vehicle, for example the control of the speed, the trajectory, etc.

[0003] Some of the AD AS systems use data obtained from one or more sensors on board the vehicle which make it possible to obtain data on the vehicle's environment, for example data on the presence of obstacles, other vehicles, road signs, etc.

[0004] The behavior of a vehicle traveling in an environment comprising one or more other vehicles in circulation can thus vary depending on whether the vehicle and the other vehicle(s) traveling around it are configured or not to travel in an autonomous or semi-autonomous driving mode, that is to say whether or not each of these vehicles is provided with a driving automation function.

[0005] It may thus prove important for a vehicle traveling in a road environment to know whether the vehicles traveling around it are configured to travel according to a determined level of autonomy, for example to improve the safety of this vehicle and of other road users. Summary of the present invention

[0006] An object of the present invention is to solve at least one of the problems of the technological background described above.

[0007] Another object of the present invention is to enable the determination of the level of autonomy of a third-party vehicle circulating in the environment of an ego-vehicle.

[0008] Another object of the present invention is to improve the safety of a vehicle circulating in a specific environment.

[0009] According to a first aspect, the present invention relates to a method for determining a level of autonomy of a second vehicle traveling in an environment of a first vehicle, the method comprising the following steps: - obtaining, by the first vehicle, data representative of the second vehicle from at least one device on board the first vehicle, the data corresponding to: • first data representative of at least one image of the second vehicle acquired by an on-board camera of the first vehicle, and / or • second data representative of characteristics of the second vehicle received from the second vehicle by the first vehicle via a first wireless connection; - determination, by data processing, of at least two pieces of information representative of the second vehicle from among: • initial information representing the registration of the second vehicle, • a second piece of information representative of a make, model and / or type of the second vehicle, • a third piece of information representing inscriptions affixed to the second vehicle, and • a fourth piece of information representing the capacity of the second vehicle to drive in an autonomous or semi-autonomous driving mode; - determination of the level of autonomy of the second vehicle and a confidence index associated with the level of autonomy determined from at least two pieces of information.

[0010] Such a method makes it possible to determine the level of autonomy of a third-party vehicle (the second vehicle) by an ego-vehicle (the first vehicle), the level of autonomy reflecting the capacity of the third-party vehicle to travel in an autonomous mode, with a determined degree of autonomy, or without any autonomy, that is to say without any assistance from a driving assistance system. The determination of the level of autonomy is made possible by data acquired by the first vehicle, which data are representative of distinctive characteristics of the third-party vehicle.

[0011] Knowing the level of autonomy of the third-party vehicle, the ego-vehicle is thus, for example, able to adapt its behavior to the level of autonomy of the third-party vehicle, which makes it possible to improve the safety of the ego-vehicle in particular, for example by anticipating certain control parameters of the third-party vehicle such as, for example, the distance separating the third-party vehicle from the ego-vehicle.

[0012] According to a variant, the determination of the level of autonomy comprises a classi classification of the second vehicle in a class belonging to a set of classes comprising: - a first representative class of non-autonomous vehicles having a level of autonomy equal to 0; - a second representative class of semi-autonomous vehicles having a level of autonomy less than or equal to a first threshold; - a third representative class of fully autonomous vehicles having a level of autonomy strictly higher than the first threshold, the third class comprising a first subclass representative of dual-mode vehicles and a second subclass representative of non-dual-mode vehicles.

[0013] According to another variant, the method further comprises a step of controlling a set of driving assistance systems comprising at least one driving assistance system of the first vehicle as a function of the level of autonomy of the second vehicle and the associated confidence index.

[0014] According to an additional variant, the method further comprises the following steps: - determination of a fifth piece of information representing the identification of a group of vehicles to which the second vehicle belongs among a set of groups of vehicles from the first piece of information and / or the second piece of information; - determination of a first level of danger of the second vehicle from the fifth information and from a database associating a reference level of danger with each group of vehicles of the set of groups of vehicles, the reference level of danger associated with each group being determined from historical data of accidents and / or incidents of vehicles belonging to each group.

[0015] According to another variant, the method further comprises the following steps: - determination of third data representative of dangerous behaviors of the second vehicle in the environment detected from fourth data representative of behavior of the second vehicle obtained from at least one environment perception sensor on board the first vehicle; - determination of a sixth piece of information representative of an occurrence of dangerous behavior from the third data; - determination of a second level of danger for the second vehicle based on the sixth information.

[0016] According to an additional variant, the set of driving assistance systems is further controlled as a function of the first level of danger and / or the second level of danger.

[0017] According to another variant, the method further comprises the following steps: - generation of fifth data representative of a dangerous behavior report from the third data; - transmission of the fifth data to a remote device via a second wireless connection.

[0018] According to a second aspect, the present invention relates to a device for determining a level of autonomy of a second vehicle traveling in an environment of a first vehicle, the device comprising a memory associated with a processor configured for implementing the steps of the method according to the first aspect of the present invention.

[0019] According to a third aspect, the present invention relates to a vehicle, for example of the automobile type, comprising a device as described above according to the second aspect of the present invention.

[0020] According to a fourth aspect, the present invention relates to a computer program which comprises instructions adapted for executing the steps of the method according to the first aspect of the present invention, in particular when the computer program is executed by at least one processor.

[0021] Such a computer program may use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0022] According to a fifth aspect, the present invention relates to a computer-readable recording medium on which is recorded a computer program comprising instructions for carrying out the steps of the method according to the first aspect of the present invention.

[0023] On the one hand, the recording medium may be any entity or device capable of storing the program. For example, the medium may comprise a storage means, such as a ROM memory, a CD-ROM or a microelectronic circuit type ROM memory, or a magnetic recording means or a hard disk.

[0024] Furthermore, this recording medium may also be a transmissible medium such as an electrical or optical signal, such a signal being able to be conveyed via an electrical or optical cable, by conventional or hertzian radio or by self-directed laser beam or by other means. The computer program according to the present invention may in particular be downloaded from an Internet-type network.

[0025] Alternatively, the recording medium may be an integrated circuit in which the computer program is incorporated, the integrated circuit being adapted to perform or to be used in performing the method in question. Brief description of the figures

[0026] Other characteristics and advantages of the present invention will emerge from the description of the particular and non-limiting exemplary embodiments of the present invention below, with reference to the appended figures 1 to 4, in which:

[0027] [Fig-1] schematically illustrates an environment of a first vehicle, according to a particular and non-limiting example of embodiment of the present invention;

[0028] [Fig.2] illustrates a flowchart of the different operations of a process for determining a level of autonomy of a second vehicle circulating in the environment of the first vehicle of [Fig.l], according to a particular and non-limiting exemplary embodiment of the present invention.

[0029] [Fig.3] schematically illustrates a device configured to determine a level of autonomy of a second vehicle traveling in the environment of the first vehicle of [Fig.1], according to a particular and non-limiting exemplary embodiment of the present invention;

[0030] [Fig.4] illustrates a flowchart of the different steps of a method for determining a level of autonomy of a second vehicle traveling in the environment of the first vehicle of [Fig.l], according to a particular and non-limiting exemplary embodiment of the present invention. Description of examples of implementation

[0031] A method and a device for determining a level of autonomy of a second vehicle traveling in an environment of a first vehicle will now be described in what follows with joint reference to Figures 1 to 4. The same elements are identified with the same reference signs throughout the description which follows.

[0032] The terms "first(s)", "second(s)" (or "first(s)", "second(s)"), etc. are used in this document by arbitrary convention to enable different elements (such as operations, means, etc.) implemented in the embodiments described below to be identified and distinguished. Such elements may be distinct or correspond to a single element, depending on the embodiment.

[0033] According to a particular and non-limiting example of embodiment of the present invention, the determination of a level of autonomy of a second vehicle traveling in the same environment as a first vehicle allows the vehicle to determine whether the second vehicle has automation function(s) allowing the second vehicle to travel autonomously or semi-autonomously or not.

[0034] The determination of the level of autonomy of the second vehicle is implemented by one or more computers of the first vehicle. According to an alternative embodiment, the determination is implemented by a system comprising one or more dis remote data processing devices, such as servers, and one or more computers of the first vehicle, the latter being connected in wireless communication with the remote data processing device(s).

[0035] Determining the level of autonomy of the second vehicle comprises obtaining, by the first vehicle, data representative of the second vehicle received from one or more devices on board the first vehicle, for example one or more cameras and / or a TCU (Telematic Control Unit) type communication unit. These data are representative of characteristics of the second vehicle and comprise first data representative of at least one image of the second vehicle and / or second data representative of characteristics of the second vehicle received from the second vehicle via a wireless connection, for example of the V2X (Vehicle-to-everything) type, for example V2V (Vehicle-to-Vehicle) type.

[0036] At least two pieces of information representative of the second vehicle are determined by processing the data obtained, from among the following pieces of information: a first piece of information representative of a registration of the second vehicle, a second piece of information representative of a make, a model and / or a type of the second vehicle, a third piece of information representative of inscriptions affixed to the second vehicle, and a fourth piece of information representative of a capacity of the second vehicle to circulate according to an autonomous or semi-autonomous driving mode.

[0037] These two or more pieces of information are processed to determine information representative of the level of autonomy of the second vehicle reflecting the capacity of the second vehicle to travel or not with the assistance of one or more ADAS systems.

[0038] [Fig. 1] schematically illustrates an environment 1 in which a first vehicle 11 moves, according to a particular and non-limiting exemplary embodiment of the present invention.

[0039] The first vehicle 11 corresponds for example to a vehicle with a thermal engine, with electric motor(s) or even a hybrid vehicle with a thermal engine and one or more electric motors. The first vehicle 11 thus corresponds for example to a land vehicle, for example a car, a truck, a bus.

[0040] The environment 1 further comprises one or more second vehicles 12. A second vehicle 12 corresponds for example to a vehicle detected by the first vehicle 11, either by one or more environmental perception sensors on board the first vehicle 11, or by signaling data transmitted by the second vehicle 12 and received, directly or indirectly via a wireless communication infrastructure, by the first vehicle 11 via a connection wireless.

[0041] The second vehicle 12 also corresponds to a vehicle with a thermal engine, with an electric motor(s) or even a hybrid vehicle with a thermal engine and one or more electric motors. The second vehicle 12 thus also corresponds to a land vehicle, for example an automobile, a truck, a bus.

[0042] The first vehicle 11 corresponds to a vehicle configured to travel under the control of the driver and / or under the control of one or more AD AS systems supplied with data by devices and sensors associated with the AD AS systems.

[0043] According to a first embodiment, the first vehicle 11 corresponds to a vehicle adapted to circulate in an autonomous or semi-autonomous driving mode, that is to say under the partial or total supervision of one or more AD AS systems embedded in the first vehicle 11. The first vehicle 11 is for example configured to circulate in the environment 1 with a level of autonomy greater than or equal to 3 or 4 according to the scale defined by the American federal agency which has established 5 levels of autonomy ranging from 1 to 5, level 0 corresponding to a vehicle having no autonomy, the driving of which is under the total supervision of the driver, and level 5 corresponding to a completely autonomous vehicle.

[0044] According to a second embodiment, the first vehicle 11 corresponds to a vehicle not adapted to circulate in an autonomous or semi-autonomous driving mode, the first vehicle 11 circulating under the total control of the driver without assistance from an AD AS system, with a level of autonomy equal to 0 (no automation, the driver of the vehicle totally controls the main functions of the vehicle (engine, accelerator, steering, brakes)).

[0045] The 5 levels of autonomy of the classification of the federal agency responsible for road safety are: - level 1: driver assistance, automation is active for certain vehicle functions, the driver retaining overall control over the vehicle's driving; cruise control is part of this level, as are other aids such as ABS (anti-lock braking system) or ESP (programmed electro-stabilizer); - level 2: automation of combined functions, the control of at least two main functions is combined in the automation to replace the driver in certain situations; for example, adaptive cruise control combined with lane centering allows a vehicle to be classified as level 2, as does automatic parking assistance (from the English “Park assist”); - level 3: limited autonomous driving, the driver can cede complete control of the vehicle to the automated system which will then be in charge of critical safety functions; autonomous driving can however only take place in certain specific environmental and traffic conditions (only on motorways, for example); - level 4: fully autonomous driving under certain conditions, the vehicle is designed to ensure all critical safety functions on its own over a complete journey; the driver provides a destination or navigation instructions but is not required to make himself available to take back control of the vehicle; - level 5: completely autonomous driving without driver assistance in all circumstances.

[0046] The classification of the International Organization of Motor Vehicle Manufacturers is similar to that listed above, except that it has 6 levels, with level 3 of the American classification being divided into 2 levels in that of the International Organization of Motor Vehicle Manufacturers.

[0047] According to the first particular embodiment, the first vehicle 11 carries one or more ADAS systems each controlled by one or more computers. These computers form, for example, a multiplexed architecture for the performance of various services useful for the proper functioning of the vehicle and for assisting the driver and / or the passengers of the vehicle in controlling the first vehicle 11 via the control of the ADAS system(s) on board the first vehicle 11.The computers communicate and exchange data with each other via one or more computer buses, for example a communication bus of the data bus type CAN (from the English "Controller Area Network" or in French "Réseau de contrôles"), CAN FD (from the English "Controller Area Network Flexible Data-Rate" or in French "Réseau de contrôles à débit de données flexible"), FlexRay (according to the ISO 17458 standard), LIN (from the English "Local Interconnect Network" or in French "Réseau interconnecté local") or Ethernet (according to the ISO / IEC 802-3 standard).

[0048] The ADAS system(s) embedded in the first vehicle 11 correspond for example to one or more of the ADAS systems from the following list, this list being non-exhaustive and provided for illustration purposes: - navigation and geolocation system, also called GNSS system (Geolocation and Navigation by a Satellite System), for example a GPS type system (from the English “Global Positioning System” or in French “Geo-positioning system by satellites”); - a speed control system, for example an adaptive cruise control system, known as an ACC system (from the English “Adaptive Cruise Control”); - a lane keeping assistance system, known as the LKA system (from the English “Lane Keeping Assist”); - an involuntary lane departure warning system, known as the AFIL system; and / or - a traffic sign reading / recognition system, known as the system TSR (from the English “Traffic Sign Recognition”); - a semi-automatic lane change system, known as the SALC system (from the English “Semi-Automatic Lane Change”); - a system for detecting and recognizing road markings.

[0049] One or more of these systems operate on the basis of data received from a data receiving device (for example a GNSS system data receiver) and / or from sensors such as radar(s), lidar(s) and / or cameras.

[0050] The sensor(s) associated with these AD AS systems correspond, for example, to one or more of the following sensors: - one or more millimeter wave radars arranged on the first vehicle 11, for example at the front, at the rear, on each front / rear corner of the vehicle; each radar is adapted to emit electromagnetic waves and to receive the echoes of these waves returned by one or more objects, for the purpose of detecting obstacles and their distances from the first vehicle 11; and / or - one or more LIDAR(s) (from the English “Light Detection And Ranging”, or “Light Detection and Ranging” in French), a LIDAR sensor corresponding to an optoelectronic system composed of a laser emitting device, a receiving device comprising a light collector (to collect the part of the light radiation emitted by the emitter and reflected by any object located in the path of the light rays emitted by the emitter) and a photodetector which transforms the collected light into an electrical signal; a LIDAR sensor thus makes it possible to detect the presence of objects located in the emitted light beam and to measure the distance between the sensor and each detected object; and / or - one or more cameras (associated or not with a depth sensor) for acquiring one or more images of the environment around the first vehicle 11 located in the field of vision of the camera(s), for example a so-called front camera, such a front camera being arranged in the passenger compartment of the first vehicle 11 under the windshield and at the top and in the middle of this windshield and having a field of vision corresponding to the space located in front of the first vehicle 11 according to the direction of travel of the first vehicle 11.

[0051] The first vehicle 11 is advantageously configured to communicate (receive and / or transmit) data with other vehicles and / or an infrastructure of a communication network according to a wireless communication mode, called V2X.

[0052] For this purpose, the first vehicle 11 carries a communication device corresponding for example to a telematic control unit, called TCU (from the English “Telematic Control Unit”) associated with one or more antennas.

[0053] The environment 1 of the first vehicle 11 comprises for example a mobile communication infrastructure, for example an infrastructure of a V2X type network (of the English "Vehicle-to-everything" or in French "Vehicle to everything"), with which the first vehicle 11 is configured to communicate data. The communication infrastructure 1 implements for example communications according to the LTE (Long-Term Evolution) technology, LTE-Avanced (Long-Term Evolution -Advanced) or C-V2X (Cellular - Vehicle to Everything) which is based on 4G and / or 5G, based on LTE. The first vehicle 11 advantageously communicates using a so-called V2X communication system, for example based on the 3GPP LTE-V or IEEE 802.1 lp standards of ITS G5.In such a V2X communication system, each vehicle carries a node to enable vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and / or vehicle-to-pedestrian (V2P) communication.

[0054] The network infrastructure comprises, for example, communication devices 110 corresponding to relay antennas and / or roadside units (RUs), each corresponding to a node of the network.

[0055] The antenna or UBR 110 is advantageously connected to one or more remote servers 111, for example via the “cloud” 100 (or in French “nuage”), via a wired and / or wireless connection. The antenna or UBR 110 is thus configured to act as a relay between the “cloud” 100 (and the remote server 111) and the first vehicle 11.

[0056] Different embodiments of a process for determining a level of autonomy of each second vehicle 12 of a set of second vehicles circulating in an environment of the first vehicle 11 are illustrated in [Fig.2].

[0057] The operations associated with certain particular embodiments are illustrated with dotted lines.

[0058] The process is for example implemented by one or more processors of one or more computers of the first vehicle 11. According to an alternative embodiment, the process is implemented by a system comprising one or more computers of the first vehicle 11 and one or more remote data processing devices such as the remote device 111, these different elements being connected in wireless communication.

[0059] The process is described for a single second vehicle 12 detected by the first vehicle 11, for example via one or more perception sensors (radar, lidar, camera) on board the first vehicle 11 and / or by data transmitted by the second vehicle 12 and received by the first vehicle 11 (either according to a direct communication mode according to a wireless connection between the first vehicle 11 and the second vehicle 12, or via the infrastructure of the wireless communication network).

[0060] The process applies identically to any second vehicle detected in the environment of the first vehicle 11.

[0061] In a first operation 21, data representative of the second vehicle 12 are obtained by the first vehicle 11 from one or more devices on board the first vehicle 11, for example from one or more cameras on board the first vehicle 11 and / or from a TCU type communication unit on board the first vehicle 11.

[0062] The camera(s) of the first vehicle 11 are each configured for the acquisition of images of the external environment surrounding the first vehicle 11, for example a front camera configured for the acquisition of images of the environment located in front of the first vehicle 11 and optionally a rear camera configured for the acquisition of images of the environment located behind the first vehicle 11 and / or side cameras configured for the acquisition of images of the environment located on the left and right sides of the first vehicle 11.

[0063] The data obtained include: - first data representative of one or more images of the second vehicle 12 acquired by one or more on-board cameras of the first vehicle 11: the image(s) represent the second vehicle 12 from one or more points of view (depending on the number of cameras acquiring the images and / or depending on the movements of the first vehicle 11 and the second vehicle 12 relative to each other); the first data correspond for example to data representative of RGB values ​​(from the English “Red, Green, Blue” or in French “Rouge, vert, bleu”) associated with each pixel of each image; and / or - second data representative of characteristics of the second vehicle 12 received from the second vehicle 12 by the first vehicle 11 via a first wireless connection, for example via a direct wireless connection between the first vehicle 11 and the second vehicle 12 (for example according to a V2V communication mode) or via the wireless communication infrastructure (for example according to a V2I communication mode).

[0064] In a second operation 22, the data obtained in the first operation 21 are analyzed and / or processed to determine at least two pieces of information representative of the second vehicle 12 from among the following pieces of information: - a first piece of information representative of a registration of the second vehicle, determined for example by any image processing method applied to the first data (in particular when the camera having acquired the first data corresponds to a front camera or a rear camera), for example a method of the LAPI (Automated License Plate Reading) type; according to a variant, the first piece of information is obtained from the second data transmitted by the second vehicle 12 which include this information, for example upon request issued by the first vehicle 11 or automatically at regular intervals according to a V2V or V2I wireless communication mode; - a second piece of information representative of a make, a model and / or a type of the second vehicle, this second piece of information being for example determined by an image processing method (reading characters and / or logos written for example on the rear of the second vehicle 12) and / or by a classification method according to for example the silhouette and / or distinctive visual characteristics of the second vehicle, a classification method being for example implemented by a neural network; according to a variant, the second piece of information is obtained from the second data transmitted by the second vehicle 12 which include this information, for example upon request transmitted by the first vehicle 11 or automatically at regular intervals according to a V2V or V2I wireless communication mode; - a third piece of information representing inscriptions affixed to the second vehicle, for example inscriptions intended to inform other road users that the second vehicle 12 is an autonomous vehicle traveling in an autonomous driving mode (under the full control of the AD AS systems), such inscriptions being for example required by regulation for this type of vehicle in certain countries such as Singapore or in certain states of the USA where autonomous vehicles are provided with specific registration plates;and - a fourth piece of information representative of a capacity of the second vehicle to travel according to an autonomous or semi-autonomous driving mode, such a fourth piece of information being obtained from the second data transmitted by the second vehicle 12, this fourth piece of information corresponding for example to the level of autonomy of the vehicle (for example a level between 1 and 5) or to information relating to a class of vehicles to which the second vehicle 12 belongs, each class being representative of a different level of autonomy.;

[0065] The data processing is for example implemented by one or more computers of the first vehicle 11.

[0066] According to an alternative embodiment, the data processing is implemented by a device unloaded from the first vehicle 11 such as a server 111 of the “cloud” 100. According to this alternative, the first vehicle 11 transmits the data to the server 111 via a wireless connection, the server 111 processes the received data. The server 111 transmits in return the result of the processing to the first vehicle 11 via the wireless connection or uses the information thus determined to determine the level of autonomy of the second vehicle 12 and a confidence index associated with the determination of the level of autonomy, as described below, before transmitting to the first vehicle 11 the data representative of the level of autonomy as well as determined.

[0067] In a third operation 23, a level of autonomy of the second vehicle 12 and a confidence index associated with the determined level of autonomy are determined from the two or more pieces of information obtained in the second operation 22.

[0068] The determination of the level of autonomy and the associated confidence index are determined by the first vehicle 11 or by the server 111 which then transmits the result of the determination to the first vehicle 11 via the wireless connection linking the server 111 to the first vehicle 11.

[0069] The level of autonomy corresponds for example to a level whose value is between 0 (no autonomy possible, i.e. no automation function on board the first vehicle 11) and 5 or 6 (circulation in complete autonomy, without any supervision of the driver), depending on the classification used.

[0070] According to another example, the level of autonomy identifies a class in a set of classes, each class of the set of classes being associated with a type of vehicle according to its level or degree of autonomy. According to this example, the determination of the level of autonomy comprises the classification of the first vehicle 11 to associate it with the class to which it belongs according to its level of autonomy determined according to the two or more pieces of information obtained in the second operation.

[0071] According to this example, the class set includes the following classes: - a first representative class of non-autonomous vehicles having a level of autonomy equal to 0; - a second representative class of semi-autonomous vehicles having a level of autonomy less than or equal to a first threshold (the first threshold being for example equal to 4 according to the classification described previously and comprising 5 levels); - a third representative class of fully autonomous vehicles having a level of autonomy strictly higher than the first threshold, the third class comprising a first subclass representative of dual-mode vehicles and a second subclass representative of non-dual-mode vehicles.

[0072] According to a variant, the number of classes is equal to 4, as follows: - a first representative class of non-autonomous vehicles having a level of autonomy equal to 0; - a second representative class of semi-autonomous vehicles having a level of autonomy less than or equal to a first threshold; - a third representative class of fully autonomous dual-mode vehicles with a level of autonomy strictly higher than the first threshold; and - a fourth representative class of non-dual-mode, fully autonomous vehicles with a level of autonomy strictly higher than the first threshold.

[0073] A dual-mode vehicle is defined in Implementing Regulation EU 2022 / 1426 of 26 August 2022 of the European Commission. A dual-mode vehicle corresponds to a fully automated vehicle with a conventional driving position, i.e. a vehicle having a driver's seat, the dual-mode vehicle being designed and constructed for: (a) be driven by the driver in a so-called manual driving mode, i.e. under the driver's supervision; and (b) be driven by the automated driving system without any driver supervision in a so-called fully automated or autonomous driving mode.

[0074] A non-dual-mode vehicle corresponds to a completely automated or autonomous vehicle without a conventional driving position.

[0075] The first information representative of the registration plate is for example used to query a database (stored for example locally in a memory of the first vehicle 11 and updated regularly from a server such as the server 111 via the wireless connection or stored in a remote device of the “cloud” 100 such as the server 111) and obtain in return the level of autonomy. Such a database is for example updated by the automobile manufacturers in conjunction with the administrations controlling the registrations of the vehicles.

[0076] In the same way, the second information representative of the make, model or type of vehicle is used to query a database (local in the first vehicle or remote) and obtain in return the level of autonomy. Such a database is for example updated by automobile manufacturers. For example, certain vehicle models can be associated with a determined level of autonomy or a minimum level of autonomy, which makes it possible to obtain information on the level of autonomy knowing the model and the make of the vehicle. In the same way, certain vehicle makes can only build vehicles with a determined or minimum level of autonomy, which makes it possible to obtain information on the level of autonomy knowing the make.Finally, certain types of vehicle such as an automated urban shuttle (noted NA-VURBAUTO) are for example identified as being a vehicle with a determined or minimal level of autonomy.

[0077] A probability level that the vehicle is provided with automation functions is for example further associated with certain models, this probability level being stored in the database with the information on the level of autonomy.

[0078] The use of at least two pieces of information among the first, second, third and fourth pieces of information to determine the level of autonomy of the second vehicle 12 makes it possible to determine a level of confidence (for example a value between 0 and 1, 0 corresponding to the minimum level and 1 to the maximum level) associated with the determination of the level of autonomy. For example, when the level of autonomy determined from each piece of information is identical, then the associated confidence level is high or maximum (for example equal to 1 or greater than 0.9). Conversely, the determination of different levels of autonomy according to the information results in a lower level of confidence, the level of confidence being all the lower the higher the difference between 2 levels of autonomy obtained.

[0079] According to an alternative embodiment, the confidence level is determined or calculated by further considering the probability level associated with the autonomy level, where applicable.

[0080] When two or more different autonomy levels are obtained, the lowest autonomy level is for example selected and associated with the second vehicle 12.

[0081] In a fourth operation 24, a set of driving assistance systems comprising at least one driving assistance system of the first vehicle 11 is controlled as a function of the level of autonomy of the second vehicle 12 and the associated confidence index determined in the third operation 23.

[0082] The associated system(s) thus controlled depend for example on the level of autonomy of the first vehicle 11 and / or the driving assistance systems on board the first vehicle 11.

[0083] When the first vehicle 11 has an autonomy level equal to 0 or 1, that is to say with no AD AS system configured to assist the driver in controlling the vehicle, then the control of the set of driving assistance systems of the first vehicle 11 comprises the automatic generation and rendering of alerts, information and / or driving instructions intended for the driver of the first vehicle 11. The driving assistance system thus controlled corresponds to a display system and / or a voice or sound rendering system on board the first vehicle 11 for displaying and / or rendering by voice synthesis the alerts and / or driving instructions generated.

[0084] For example, driving instructions or recommendations recommending that the driver adapt the inter-vehicle distance (or inter-vehicle time) between the first and second vehicles are generated, the distance varying according to the level of autonomy of the second vehicle 12. For example, it may be considered that the higher the level of autonomy of the second vehicle 12, the more its behavior is predictable and compliant with the highway code. Thus, the inter-vehicle distance may be all the lower (with a minimum not to be exceeded for safety reasons) as the level of autonomy is high and the level of confidence is high.

[0085] According to other examples, recommendations for exceeding the second vehicle 12, changing lane, can be made according to the determined autonomy level of the second vehicle 12.

[0086] When the first vehicle 11 has an autonomy level equal to 2, 3 or more, that is to say when the first vehicle 11 is equipped with one or more AD AS systems configured to assist the driver in controlling the vehicle, then the control of the set of driving assistance systems of the first vehicle 11 comprises the control of at least one AD AS system, for example the ACC system or the SALC system. The control of a SALC system comprises for example the adjustment of the value of a control parameter of the system, for example the set inter-vehicle time for an ACC system or a speed when overtaking the second vehicle 12 controlled by the SALC system.The value of the set inter-vehicle time parameter is for example adjusted downwards when the autonomy level of the second vehicle is greater than a threshold (for example greater than 3 or if the second vehicle belongs to one of the second, third or fourth classes) and the confidence level is greater than a threshold (for example greater than 0.8) and maintained at its default value or adjusted upwards when the autonomy level of the second vehicle is lower than the threshold and / or the confidence level is lower than the threshold.

[0087] According to a particular embodiment, the process further comprises a set of operations 25 according to which: - a fifth piece of information representing the identification of a group of vehicles to which the second vehicle belongs among a set of groups of vehicles is determined from the first piece of information and / or the second piece of information; and - a first level of danger of the second vehicle is determined from the fifth information and from a database associating a reference level of danger with each group of vehicles of the set of vehicle groups, the reference level of danger associated with each group being determined from historical data of accidents and / or incidents of vehicles belonging to each group.

[0088] According to this particular embodiment, the second vehicle 12 is for example identified from the first information representative of its registration plate obtained by image processing and / or from the second information representative of the make, model and / or type of the second vehicle 12.

[0089] Such a fifth piece of information makes it possible to identify to which group of vehicles the second vehicle 12 belongs, a group of vehicles comprising, for example, vehicles of the same model of the same make or vehicles of the same type (for example, vehicles of the van, utility, NA- type). VURBAUTO, etc.).

[0090] The fifth information is used to query a database (local in the first vehicle or remote in the “cloud” 100) and obtain in return information representative of a level of danger, called reference, associated with the group to which the second vehicle 12 belongs. Such a database is for example updated by automobile manufacturers.

[0091] A danger level (or a risk level) is determined for each group of vehicles from historical data of accidents and / or incidents of vehicles belonging to this group, for example based on the number of occurrences of incidents and / or accidents recorded (for example over a given time interval, for example over the past 5 or 10 years). Indeed, manufacturers of autonomous or automated vehicles are required at European level to produce reports related to the operation of autonomous or automated vehicles and administrations are required to establish a mandatory reporting system for incidents or accidents for autonomous vehicles. The historical data are thus analyzed to determine, for each group of vehicles, a reference danger level.

[0092] A first level of danger (or first level of risk) is associated with the second vehicle 12, this first level of danger corresponding to the reference level of danger of the group of vehicles to which the second vehicle 12 belongs.

[0093] According to this embodiment, the first level of danger is taken into account for the control of the on-board system(s) of the first vehicle 11 in operation 24, in addition to the level of autonomy and the associated level of confidence.

[0094] According to another particular embodiment, the process further comprises a set of operations 26 according to which: - third data representative of dangerous behaviors of the second vehicle 12 in the detected environment 1 are determined from fourth data representative of behavior of the second vehicle 12 obtained from at least one environment perception sensor on board the first vehicle H; - a sixth piece of information representative of an occurrence of dangerous behavior is determined from the third data; and - a second level of danger of the second vehicle is determined from the sixth information.

[0095] According to this other embodiment, the fourth data acquired by one or more environmental perception sensors (camera, radar and / or lidar) on board the first vehicle 11 are processed / analyzed to detect one or more dangerous behaviors of the second vehicle 12 from the moment when the second vehicle 12 was detected by the first vehicle 11.

[0096] Dangerous behavior corresponds, for example, to an action or maneuver of the second vehicle 12 that does not comply with a rule of a set of rules, such as, for example, the rules of the highway code.

[0097] Dangerous behavior corresponds, for example, to a behavior or event from the non-exhaustive list below: - Deviation from trajectory (slow or sudden), leading to partial or total departure from the lane, - Weaving in the track, - Accelerations beyond a certain threshold, - Deceleration beyond a certain threshold, - Speeding beyond the legal limit, - Speed ​​below a certain threshold, in relation to the legal limit, - Inappropriate stopping / parking distance on the road, - Inter-vehicle distance (or inter-vehicle time) below a determined threshold, - Dangerously overtaking a vehicle or a vulnerable user (for example a cyclist), - Crossing a continuous line, - Fish tail, - Refusal of priority, - Going through a red light, - Traffic without lights on, - Failure (total or partial) of traffic lights, - Etc.

[0098] When such an event relates to dangerous behavior, the third data relating to the latter are recorded in the memory of the first vehicle and / or are transmitted to a remote device such as the server 111 via a wireless connection. These third data comprise, for example, an identifier of the identified dangerous behavior. According to a variant, the third data further comprise information relating to the location (for example, GPS coordinates), the time (for example, the date and time) when the detected dangerous event took place, data identifying the second vehicle 12 (for example, its registration number), one or more images of the dangerous event, the type of event and / or a value representative of the criticality or the level of danger of the dangerous behavior, etc.

[0099] The number of times a detected dangerous behavior is calculated or determined (e.g. as long as the second vehicle 12 is detected by the perception sensor(s) of the first vehicle 11) from the third data to obtain the sixth information representative of the occurrence of dangerous behaviors. This calculation is carried out by a computer of the vehicle or by the remote device receiving the third data, if applicable. This sixth information is for example also recorded in the memory of the first vehicle 11 or of the remote device.

[0100] A second level of danger of the second vehicle is determined from the sixth information, the second level of danger (for example between 0 and 1) increasing when the number of occurrences increases.

[0101] When this second level of danger is determined by a computer of the first vehicle, the data representative of this second level of danger are optionally transmitted to a remote device for archiving for example and / or to establish danger statistics per vehicle.

[0102] When this second level of danger is determined by the remote device, the data representative of this second level of danger are transmitted to the first vehicle 11 via the wireless connection.

[0103] According to this other embodiment, the second level of danger is taken into account for the control of the on-board system(s) of the first vehicle 11 in operation 24, in addition to the level of autonomy and the associated level of confidence, or even in addition to the first level of danger.

[0104] According to another embodiment, the process further comprises a set of operations 27 according to which: - fifth data representative of a dangerous behavior report are generated from the third data; and - the fifth data are transmitted to a remote device such as the server 111 via a wireless connection linking the first vehicle 11 to the “cloud” 100.

[0105] These operations are implemented by one or more computers on board the first vehicle 11 or by a remote server-type device receiving the third and / or fourth data from the first vehicle 11.

[0106] The fifth data comprises for example the type of dangerous event detected and / or information relating to the place (for example GPS coordinates), the moment (for example the date and time) when the detected dangerous event took place and / or data identifying the second vehicle 12 (for example its registration number) and / or one or more images of the dangerous event and / or a value representative of the criticality or the level of danger of the dangerous behavior.

[0107] An automatic report is automatically generated from the fifth data, for example according to a document template, to be edited according to a predefined format. The report is furthermore, for example, transmitted to a device configured to store all the reports edited from data obtained from vehicles traveling on the roads.

[0108] Such a report responds, for example, to the recommendations of the European Commission relating to NATM (from the English "New Assessment Test Methods" or in French "Nouvelles méthodes de test d'évaluation") which open the way to voluntary reporting for autonomous or automated vehicles in circulation.

[0109] Such a process makes it possible to improve the monitoring of automated vehicles in circulation by detecting these automated vehicles, and to improve road safety, via the reduction of risks during interaction with automated vehicles.

[0110] [Fig. 3] schematically illustrates a device 3 configured to determine a level of autonomy of a second vehicle traveling in an environment of a first vehicle, for example the first vehicle 11, according to a particular and non-limiting exemplary embodiment of the present invention. The device 3 corresponds for example to a device on board the first vehicle 11, for example a computer.

[0111] According to another example, the device 3 corresponds to a data processing device of the server or computer type.

[0112] The device 3 is for example configured for the implementation of the operations described with regard to figures 1 and 2 and / or the steps of the method described with regard to [Fig.4]. Examples of such a device 3 include, but are not limited to, on-board electronic equipment such as an on-board computer of a vehicle, an electronic calculator such as an ECU (“Electronic Control Unit”), a smartphone, a tablet, a laptop. The elements of the device 3, individually or in combination, can be integrated in a single integrated circuit, in several integrated circuits, and / or in discrete components. The device 3 can be produced in the form of electronic circuits or software (or computer) modules or even a combination of electronic circuits and software modules.

[0113] The device 3 comprises one (or more) processor(s) 30 configured to execute instructions for carrying out the steps of the method and / or for executing the instructions of the software(s) embedded in the device 3. The processor 30 may include integrated memory, an input / output interface, and various circuits known to those skilled in the art. The device 3 further comprises at least one memory 31 corresponding for example to a volatile and / or non-volatile memory and / or comprises a memory storage device which may comprise volatile and / or non-volatile memory, such as EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, magnetic or optical disk.

[0114] The computer code of the embedded software(s) comprising the instructions to loaded and executed by the processor is for example stored in memory 31.

[0115] According to various particular and non-limiting embodiments, the device 3 is coupled in communication with other similar devices or systems and / or with communication devices, for example a TCU (from the English “Telematic Control Unit” or in French “Telematic Control Unit”), for example via a communication bus or through dedicated input / output ports.

[0116] According to a particular and non-limiting exemplary embodiment, the device 3 comprises a block 32 of interface elements for communicating with external devices. The interface elements of the block 32 comprise one or more of the following interfaces: - RF radio frequency interface, for example Wi-Fi® type (according to IEEE 802.11), for example in the 2.4 or 5 GHz frequency bands, or Bluetooth® type (according to IEEE 802.15.1), in the 2.4 GHz frequency band, or Sigfox type using UBN (Ultra Narrow Band) radio technology, or LoRa in the 868 MHz frequency band, LTE (Long-Term Evolution), LTE-Advanced; - USB interface (from the English “Universal Serial Bus” or “Universal Serial Bus” in French); - HDMI interface (from the English “High Definition Multimedia Interface” or “High Definition Multimedia Interface” in French); - LIN interface (from the English “Local Interconnect Network”).

[0117] According to another particular and non-limiting exemplary embodiment, the device 3 comprises a communication interface 33 which makes it possible to establish communication with other devices (such as other computers of the on-board system) via a communication channel 330. The communication interface 33 corresponds for example to a transmitter configured to transmit and receive information and / or data via the communication channel 330. The communication interface 33 corresponds for example to a wired network of the CAN (Controller Area Network) type, CAN FD (Controller Area Network Flexible Data-Rate), FlexRay (standardized by the ISO 17458 standard) or Ethernet (standardized by the ISO / IEC 802-3 standard).

[0118] According to a particular and non-limiting exemplary embodiment, the device 3 can provide output signals to one or more external devices, such as a display screen 340, touch-sensitive or not, one or more speakers 350 and / or other peripherals. 360 spherical (projection system) via output interfaces 34, 35 and 36 respectively. According to a variant, one or other of the external devices is integrated into the device 3.

[0119] [Fig.4] illustrates a flowchart of the different steps of a method for determining a level of autonomy of a second vehicle traveling in an environment of a first vehicle, for example the first vehicle 11, according to a particular and non-limiting exemplary embodiment of the present invention. The method is for example implemented by a device on board the first vehicle 11 or by a system comprising one or more devices on board the first vehicle 11 and one or more remote devices such as servers connected in wireless communication to the first vehicle 11.

[0120] In a first step 41, data representative of the second vehicle are obtained by the first vehicle from at least one device on board the first vehicle, the data corresponding to: • first data representative of at least one image of the second vehicle acquired by an on-board camera of the first vehicle, and / or • second data representative of characteristics of the second vehicle received from the second vehicle by the first vehicle via a first wireless connection.

[0121] In a second step 42, at least two pieces of information representative of the second vehicle are determined by processing the data obtained in the first step 41 from among: • initial information representing the registration of the second vehicle, • a second piece of information representative of a make, model and / or type of the second vehicle, • a third piece of information representing inscriptions affixed to the second vehicle, and • a fourth piece of information representing the second vehicle's ability to drive in an autonomous or semi-autonomous driving mode.

[0122] In a third step 43, the level of autonomy of the second vehicle and a confidence index associated with the level of autonomy are determined from the at least two pieces of information.

[0123] According to a variant, the variants and examples of the operations described in relation to one of figures 1 and 2 apply to the steps of the method of [Fig.4].

[0124] Of course, the present invention is not limited to the exemplary embodiments described above but extends to a method for controlling the first vehicle and / or an on-board system of the first vehicle which would include secondary steps without this would be outside the scope of the present invention. The same would apply to a device configured for implementing such a method.

[0125] The present invention also relates to a vehicle, for example an automobile or more generally an autonomous land-based motor vehicle, comprising the device 3 of [Fig.3] or a system comprising the first vehicle and one or more remote devices connected in wireless communication to the first vehicle.

Claims

Claims

1. Method for determining a level of autonomy of a second vehicle (12) traveling in an environment of a first vehicle (11), said method comprising the following steps: - obtaining (21, 41), by said first vehicle (11), data representative of said second vehicle (12) from at least one device on board said first vehicle (11), said data corresponding to: • first data representative of at least one image of said second vehicle (12) acquired by an on-board camera of said first vehicle (11), and / or • second data representative of characteristics of said second vehicle (12) received from said second vehicle (12) by said first vehicle (11) via a first wireless connection; - determination (22, 42), by processing said data, of at least two pieces of information representative of said second vehicle (12) from among: • initial information representing the registration of said second vehicle, • a second piece of information representative of a make, model and / or type of said second vehicle, • a third piece of information representing inscriptions affixed to said second vehicle, and • a fourth piece of information representing the capacity of said second vehicle to drive in an autonomous or semi-autonomous driving mode; - determination (23, 43) of said level of autonomy of the second vehicle (12) and of a confidence index associated with the level of autonomy determined from said at least two pieces of information.

2. The method of claim 1, wherein said determination of the level of autonomy comprises a classification of said second vehicle (12) into a class belonging to a set of classes comprising: - a first representative class of non-autonomous vehicles having a level of autonomy equal to 0; - a second representative class of semi-autonomous vehicles having a level of autonomy less than or equal to a first threshold; - a third representative class of completely autonomous vehicles having a level of autonomy strictly higher than said first threshold, the third class comprising a first subclass representative of dual-mode vehicles and a second subclass representative of non-dual-mode vehicles.

3. Method according to claim 1 or 2, further comprising a step of controlling (24) a set of driving assistance systems comprising at least one driving assistance system of said first vehicle (11) as a function of said level of autonomy of the second vehicle and said associated confidence index.

4. Method according to one of claims 1 to 3, further comprising the following steps (25): - determining a fifth piece of information representative of identification of a group of vehicles to which the second vehicle (12) belongs among a set of groups of vehicles from said first piece of information and / or said second piece of information; - determining a first level of danger of said second vehicle (12) from said fifth piece of information and from a database associating a reference level of danger with each group of vehicles of said set of groups of vehicles, said reference level of danger associated with each group being determined from historical data of accidents and / or incidents of vehicles belonging to said each group.

5. Method according to one of claims 1 to 4, further comprising the following steps (26): - determining third data representative of dangerous behaviors of said second vehicle (12) in said environment detected from fourth data representative of behavior of said second vehicle (12) obtained from at least one environment perception sensor on board said first vehicle (11); - determining sixth information representative of an occurrence of said dangerous behaviors from said third data; - determining a second level of danger of said second vehicle (12) from said sixth information.

6. Method according to claims 3 to 5, wherein said set of driving assistance systems is further controlled as a function of said first level of danger and / or said second level of danger. generosity.

7. Method according to claim 5, further comprising the following steps (27): - generating fifth data representative of a dangerous behavior report from said third data; - transmitting said fifth data to a remote device via a second wireless connection.

8. Computer program comprising instructions for implementing the method according to any one of the preceding claims, when these instructions are executed by a processor.

9. Device (3) for determining a level of autonomy of a second vehicle (12) traveling in an environment of a first vehicle (11), said device (3) comprising a memory (31) associated with at least one processor (30) configured for implementing the steps of the method according to any one of claims 1 to 7.

10. Vehicle (11) comprising the device (3) according to claim 9.

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