Method and device for determining the typical driving mode of a second vehicle by a first vehicle

Abstract

The present invention relates to a method and device for determining the typical driving mode 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 environmental perception sensor installed in the first vehicle (11). At least two indicators of the typical driving mode of the second vehicle (12) are determined by processing the data obtained. The typical driving mode e of the second vehicle (12) and a confidence index associated with the typical driving mode are determined from these at least two indicators. Figure 1 (for the abstract)

Description

Title of the invention: Method and device for determining a typical driving mode of a second vehicle by a first vehicle technical field

[0001] The present invention relates to methods and devices for determining the current driving mode of a second vehicle traveling in the vicinity of a first vehicle, in particular a motor vehicle. The present invention also relates to a method and device for controlling the first vehicle based on the current driving mode of the second vehicle. Technological background

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

[0003] Some AD AS systems use data obtained from one or more sensors on board the vehicle which provide 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 travelling in an environment including one or more other vehicles in circulation can thus vary depending on whether the vehicle and the other vehicle(s) travelling around it are travelling in an autonomous or semi-autonomous driving mode.

[0005] It can therefore be important for a vehicle traveling in a road environment to know whether the vehicles traveling around it are operating in manual mode (i.e., under the sole supervision of the driver) or in autonomous or partially autonomous (semi-autonomous) mode, for example, to improve the safety of that vehicle and other road users. Summary of the present invention

[0006] One 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 current driving mode of a third 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 common driving mode of a second vehicle traveling in the 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 environmental perception sensor on board the first vehicle (11), the data including: • initial representative data from at least one image of the second vehicle, and / or • second representative data for the detection of radiation emitted by the second vehicle; - determination, by data processing, of at least two indicators of the current driving mode of the second vehicle; - determination of the current driving mode of the second vehicle and a confidence index associated with the current driving mode determined from at least two indicators.

[0010] Such a method makes it possible to determine the current driving mode of a third vehicle (the second vehicle) by an ego-vehicle (the first vehicle). In particular, it makes it possible to determine whether the third vehicle is currently operating in an autonomous or automated driving mode, for example, a partially or fully autonomous driving mode. The determination of the current driving mode is obtained from the processing of data acquired by the first vehicle, which data are representative of distinctive characteristics of the second vehicle, for example, when the second vehicle is operating in an autonomous or partially autonomous driving mode.

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

[0012] According to one variant, the at least two indicators belong to a set of indicators comprising: - the presence of a specific indicator light on the second vehicle; - the absence of a person in the driver's seat of the second vehicle; - the presence of laser radiation emitted during a phase of movement of the second vehicle; and - the presence of millimeter wave radiation emitted during the movement phase of the second vehicle.

[0013] According to another embodiment, the determination of the current driving mode includes a classification of the current driving mode into a class belonging to a set of classes comprising: - a first class representative of a semi-autonomous driving mode; - a second class representing a fully autonomous, dual-mode driving system; and - a third class representing a completely autonomous, non-dual-mode driving mode.

[0014] According to a further variant, the method further includes a step of controlling a set of driver assistance systems comprising at least one driver assistance system of the first vehicle as a function of the current driving mode of the second vehicle and the associated confidence index.

[0015] According to yet another variant, the process further comprises the following steps: - determination of a first representative piece of information for identifying a group of vehicles to which the second vehicle belongs from among a set of vehicle groups based on the data; - determination of a first level of danger of the second vehicle from the first information and a database associating a reference level of danger to each group of vehicles in 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.

[0016] According to yet another variant, the process further comprises the following steps: - determination of third data representative of dangerous behavior of the second vehicle in the environment detected from the data; - determination of a second piece of information representative of an occurrence of dangerous behaviors from the third data; - determination of a second level of danger for the second vehicle based on the second piece of information

[0017] According to an additional variant, the entire set of driver assistance systems is further controlled according to the first level of danger and / or the second level of danger.

[0018] According to another variant, the process further comprises the following steps: - generation of fourth data points representative of a dangerous behavior report from the third data points; - transmission of the fourth data to a remote device via a wireless connection.

[0019] According to a second aspect, the present invention relates to a device for determining mination of a common driving mode of a second vehicle circulating in the environment of a first vehicle, the device comprising a memory associated with a processor configured for the implementation of the steps of the process according to the first aspect of the present invention.

[0020] 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.

[0021] According to a fourth aspect, the present invention relates to a computer program which includes instructions adapted for carrying out the steps of the process according to the first aspect of the present invention, in particular when the computer program is executed by at least one processor.

[0022] Such a computer program may use any programming language, and be in the form of source code, object code, or an intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0023] 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 process according to the first aspect of the present invention.

[0024] On the one hand, the recording medium can be any entity or device capable of storing the program. For example, the medium can include a storage means, such as a ROM, a CD-ROM or a microelectronic circuit-type ROM, or a magnetic recording means or a hard disk drive.

[0025] On the other hand, this recording medium can also be a transmissible medium such as an electrical or optical signal, such a signal being able to be transmitted via an electrical or optical cable, by conventional or radio frequency, by self-directing laser beam, or by other means. The computer program according to the present invention can, in particular, be downloaded from an Internet-type network.

[0026] Alternatively, the recording medium may be an integrated circuit in which the computer program is incorporated, the integrated circuit being adapted to execute or to be used in the execution of the process in question. Brief description of the figures

[0027] Other features and advantages of the present invention will become apparent from the description of the particular and non-limiting embodiments of the present invention below, with reference to the attached Figures 1 to 4, in which:

[0028] [Fig-1] schematically illustrates an environment of a first vehicle, according to a a particular and non-limiting example of a realization of the present invention;

[0029] [Fig. 2] illustrates a flowchart of the various operations of a process for determining a common driving mode of a second vehicle traveling in the vicinity of the first vehicle of [Fig. 1], according to a particular and non-limiting embodiment of the present invention.

[0030] [Fig.3] schematically illustrates a device configured to determine a common driving mode of a second vehicle traveling in the environment of the first vehicle of [Fig.1], according to a particular and non-limiting embodiment of the present invention;

[0031] [Fig.4] illustrates a flowchart of the different steps of a method for determining a common driving mode of a second vehicle traveling in the environment of the first vehicle of [Fig.1], according to a particular and non-limiting embodiment of the present invention. Description of examples of achievements

[0032] A method and device for determining a common driving mode of a second vehicle traveling in the 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 that follows.

[0033] The terms "first," "second" (or "firsts," "seconds"), etc., are used in this document by arbitrary convention to allow for the identification and distinction of different elements (such as operations, means, etc.) implemented in the embodiments described below. Such elements may be distinct or correspond to a single element, depending on the embodiment.

[0034] According to a particular and non-limiting embodiment of the present invention, determining a current driving mode, i.e. at a current time instant, of a second vehicle circulating in the same environment as a first vehicle allows the first vehicle to determine whether the second vehicle is driving in an autonomous (or automated) mode, for example a fully autonomous mode under the total supervision of the autonomous control system of the first vehicle or a partially or semi-autonomous mode under the partial supervision of the driver assisted by one or more AD AS systems.

[0035] The determination of the current driving mode of the second vehicle is implemented by one or more computers of the first vehicle. According to an embodiment, the determination is implemented by a system comprising one or more remote data processing devices, of the server type for example, and one or more computers of the first vehicle, the latter being connected by wireless communication with the remote data processing device(s).

[0036] Determining the current driving mode of the second vehicle includes obtaining, by the first vehicle, data representative of the second vehicle received from one or more perception sensors such as one or more cameras, one or more optical and / or electromagnetic radiation sensors or receivers.

[0037] At least two indicators of the current driving mode of the second vehicle are determined by processing or analyzing the data obtained. These two or more indicators are used to determine the current driving mode as well as a confidence index associated with the result of the determination of the current driving mode.

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

[0039] The first vehicle 11 corresponds, for example, to a vehicle with an internal combustion engine, with electric motor(s), or even a hybrid vehicle with an internal combustion 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 wireless connection.

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

[0042] The first vehicle 11 corresponds to a vehicle configured to circulate 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 operate 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 on board the first vehicle 11. The first vehicle 11 is for example configured to operate in 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 fully autonomous vehicle.

[0044] According to a second embodiment, the first vehicle 11 corresponds to a vehicle not adapted to operate in an autonomous or semi-autonomous driving mode, the first vehicle 11 operating 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 in 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 driving the vehicle; cruise control is part of this level, as are other aids such as ABS (anti-lock braking system) or ESP (electronic stability program); - 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 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; however, autonomous driving can only take place under certain specific environmental and traffic conditions (only on highways for example); - level 4: fully autonomous driving under certain conditions, the vehicle is designed to independently perform all critical safety functions over a complete journey; the driver provides a destination or navigation instructions but is not required to be 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, 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 providing various services useful for the proper functioning of the vehicle and for assisting the driver and / or passengers of the vehicle in controlling the first vehicle 11 via the control of the AD AS 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 CAN data bus (from the English "Controller Area Network" or in French "Réseau de contrôlers"), CAN FD (from the English "Controller Area Network Flexible Data-Rate" or in French "Réseau de contrôlers 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 AD AS system(s) on board the first vehicle 11 correspond, for example, to one or more of the AD AS systems in the following list, this list being non-exhaustive and provided for illustrative 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 "Système de géo-positionnement par satellites"); - a speed regulation system, for example an adaptive cruise control, known as ACC (Adaptive Cruise Control); - a lane keeping assist system, called LKA (from the English "Lane Keeping Assist"); - a lane departure warning system, known as an AFIL system; and / or - a traffic sign reading / recognition system, known as a TSR system (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 ground 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 environmental perception sensors of the first vehicle 11 of the radar(s), lidar(s) and / or camera type.

[0050] The environmental perception sensor(s) of the first vehicle 11 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 reflected 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) (Light Detection and Ranging), a sensor LiDAR corresponds to an optoelectronic system composed of a laser emitter, a receiver including a light collector (to collect the portion of the light emitted by the emitter and reflected by any object located in the path of the light rays emitted by the emitter), and a photodetector that 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 the acquisition of 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; - one or more sensors, receivers or detectors of optical radiation (for example laser) emitted by a vehicle other than the first vehicle, for example the second vehicle 12; - one or more sensors, receivers or detectors of electromagnetic radiation (for example millimeter waves) emitted by a vehicle other than the first vehicle, for example the second vehicle 12.

[0051] The first vehicle 11 is advantageously configured to communicate (receive and / or transmit) data with other vehicles and / or a communication network infrastructure according to a wireless communication mode, known as 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 includes, for example, a mobile communication infrastructure, for example, a V2X (Vehicle-to-Everything) network infrastructure, with which the first vehicle 11 is configured to communicate data. The communication infrastructure 1 implements, for example, communications using LTE (Long-Term Evolution), LTE-Avanced (Long-Term Evolution-Advanced), or C-V2X (Cellular-Vehicle-to-Everything) technology, which is based on 4G and / or 5G, based on LTE. The first vehicle 11 communicates advantageously 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 includes, for example, communication devices 110 corresponding to relay antennas and / or roadside units (RSUs), 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, 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 current driving mode 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 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 by 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 emitted by the second vehicle 12 and received by the first vehicle 11 (either by direct communication via a wireless connection between the first vehicle 11 and the second vehicle 12, or via the wireless communication network infrastructure).

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

[0061] In a first operation 21, representative data of the second vehicle 12 are obtained by the first vehicle 11 from one or more sensors on board the first vehicle 11, for example from one or more cameras on board the first vehicle 11 and / or from one or more optical and / or electromagnetic radiation sensors or receivers on board the first vehicle 11.

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

[0063] The data obtained include: - initial representative data from one or more images of the second vehicle 12 acquired by one or more onboard cameras of the first vehicle 11: the image(s) represent the second vehicle 12 from one or more viewpoints (depending on the number of cameras acquiring the images and / or the relative movements of the first vehicle 11 and the second vehicle 12); the initial data correspond, for example, to representative RGB (Red, Green, Blue) values ​​associated with each pixel of each image; and / or - second representative data of detection of radiation emitted by the second vehicle 12, for example optical radiation (for example emitted by one or more lidars of the second vehicle 12) or electromagnetic radiation (for example millimeter waves emitted by one or more radars of the second vehicle or radio waves emitted in the context of V2X, V2V or V2I type communication).

[0064] In a second operation 22, the data obtained in the first operation 21 are analyzed and / or processed to determine at least two indicators representative of the current driving mode of the second vehicle 12.

[0065] These two or more indicators belong to the following list of indicators: - a first indicator associated with the detection of the presence of a specified light indicator on the second vehicle, the presence of such a light indicator being detected for example by the processing of the first images: the light indicator is for example positioned on the roof of the second vehicle 12 or in several places on the body of the second vehicle 12. The light indicator takes for example several states depending on the current driving mode of the second vehicle, with for example a state in which the light source of the light indicator is off when the second vehicle 12 is driving in a manual driving mode (under the complete supervision of the driver) and a state in which the light source of the light indicator is on when the second vehicle 12 is driving in an autonomous or semi-autonomous driving mode.The color of the emitted light takes on a different color depending on the autonomous or semi-autonomous driving mode (for example, a first color for a semi-autonomous or partially autonomous driving mode and a second color for a mode of . fully autonomous driving, or a second color for a fully autonomous dual-mode driving mode and a third color for a fully autonomous non-dual-mode driving mode); - a second indicator associated with the detection of the absence of a person in the driver's seat of the second vehicle 12, the presence or absence of a person in the driver's seat (a driver sitting in the front seat on the side of the steering wheel of the second vehicle 12) being detected by the processing of the first images: the presence of the person in the driver's seat is representative of a manual, autonomous or semi-autonomous driving mode while the absence of the person in the driver's seat is representative of a (completely) autonomous, dual-mode or non-dual-mode driving mode; - a third indicator associated with the detection of optical radiation (for example laser) emitted during a phase of movement of the second vehicle 12 (and received by the first vehicle 11), this third indicator being determined by processing the second data: a detection of optical radiation is representative of the use of driver assistance devices using lidar-type sensors by the second vehicle 12 providing an indication of the use of AD AS systems and an autonomous or semi-autonomous driving mode; the absence of detection of such optical radiation is representative of the non-use of an AD AS system using lidar-type sensors at the current time by the second vehicle 12;and - a fourth indicator associated with the detection of millimeter wave radiation emitted during the movement phase of the second vehicle 12 (and received by the first vehicle 11), this fourth indicator being determined by processing the second data: a detection of millimeter wave radiation is representative of the use of driver assistance devices using radar-type sensors by the second vehicle 12 providing an indication of the use of AD AS systems and an autonomous or semi-autonomous driving mode; the absence of detection of such millimeter wave radiation is representative of the non-use of an AD AS system using radar-type sensors at the current time by the second vehicle 12.

[0066] According to one variant, the above list further includes a fifth indicator associated with the detection of radio wave radiation emitted during the movement phase of the second vehicle 12 (and received by the first vehicle 11), this fifth indicator being determined by processing the second data: a detection of radio wave radiation is for example representative of V2X, V2V or V2I type communication within the framework of an autonomous or semi-autonomous driving mode.

[0067] Data processing is, for example, implemented by one or more cal- cullers of the first vehicle 11.

[0068] According to one embodiment, data processing is carried out by a device mounted on the first vehicle 11, such as a server 111 from the "cloud" 100. In this embodiment, the first vehicle 11 transmits the data to the server 111 via a wireless connection, and the server 111 processes the received data. The server 111 then transmits the processing result back to the first vehicle 11 via the wireless connection or uses the information thus determined to determine the current driving mode of the second vehicle 12 and a confidence index associated with the determination of the current driving mode, as described below, before transmitting to the first vehicle 11 the data representing the current driving mode thus determined and the associated confidence index.

[0069] In a third operation 23, a current driving mode of the second vehicle 12 and a confidence index associated with the determined current driving mode are determined from the two or more indicators obtained in the second operation 22.

[0070] The determination of the current driving mode 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.

[0071] The current driving mode corresponds, for example, to one of the following modes: - manual driving mode, without ADAS system assistance, under the driver's full supervision (autonomy level equal to 0); and - driving mode at least partially autonomous, with or without driver supervision and with the assistance of AD AS systems (for example with an autonomy level greater than or equal to 2 or 3).

[0072] According to another example, the current driving mode corresponds, for example, to one of the following modes: - manual driving mode, without ADAS system assistance, under the driver's full supervision (autonomy level equal to 0); and - semi-autonomous (or partially autonomous) driving mode, with driver supervision and assistance from ADAS systems (for example, with an autonomy level of 2 or 3); and - fully autonomous driving mode, without driver supervision and with the assistance of AD AS systems (for example with an autonomy level of 4 or 5).

[0073] According to yet another example, the current driving mode corresponds, for example, to one of the following modes: - semi-autonomous (or partially autonomous) driving mode, with driver supervision and with the assistance of ADAS systems (for example with a level autonomy equal to 2 or 3); - fully autonomous dual-mode driving mode; - fully autonomous driving mode, not dual-mode.

[0074] Determining the current driving mode thus includes, for example, classifying the current driving mode into a class belonging to a set of classes comprising: - a first class representative of a semi-autonomous driving mode; - a second class representing a fully autonomous, dual-mode driving system; and - a third class representing a completely autonomous, non-dual-mode driving mode.

[0075] A dual-mode vehicle is defined in Commission Implementing Regulation (EU) 2022 / 1426 of 26 August 2022. A dual-mode vehicle is a fully automated vehicle with a conventional driver's cab, i.e., a vehicle with a driver's seat, the dual-mode vehicle being designed and constructed to: a) be driven by the driver in a so-called manual driving mode, that is to say, under the supervision of the driver; and b) be driven by the automated driving system without any supervision from the driver in a so-called fully automated or autonomous driving mode.

[0076] A non-dual-mode vehicle corresponds to a fully automated or autonomous vehicle without a conventional driver's seat.

[0077] Using at least two indicators to determine the current driving mode of the second vehicle 12 makes it possible to determine a confidence level (for example, a value between 0 and 1.0 corresponding to the minimum level and 1 to the maximum level) associated with determining the current driving mode. For example, when the current driving mode determined from each indicator is identical, then the associated confidence level is high or maximum (for example, equal to 1 or greater than 0.9). Conversely, determining different current driving modes according to the indicators results in a lower confidence level, the lower the confidence level the greater the difference between two current driving modes (for example, manual driving mode and fully autonomous driving mode).

[0078] When two different current driving modes are obtained, the current driving mode with the least range is for example selected and associated with the second vehicle 12.

[0079] In a fourth operation 24, a set of driver assistance systems comprising at least one driver assistance system of the first vehicle 11 is controlled according to the current driving mode of the second vehicle 12 and the associated confidence index determined in the third operation 23.

[0080] The associated system(s) thus controlled depend for example on the current driving mode of the first vehicle 11 and / or the driver assistance systems on board the first vehicle 11.

[0081] When the first vehicle 11 has an autonomy level of 0 or 1, i.e. with no AD AS system configured to assist the driver in controlling the vehicle, then the control of the set of driver assistance systems of the first vehicle 11 includes the automatic generation and rendering of alerts, information and / or driving instructions to the driver of the first vehicle 11. The driver assistance system thus controlled corresponds to a display system and / or a voice or sound rendering system on board the first vehicle 11 to display and / or render by speech synthesis the alerts and / or driving instructions generated.

[0082] For example, driving instructions or recommendations advising the driver to adjust the inter-vehicle distance (or inter-vehicle time) between the first and second vehicles are generated, the distance varying according to the current driving mode of the second vehicle 12. For example, it can be considered that the higher the level of autonomy of the second vehicle 12, the more predictable and compliant its behavior is with the rules of the road. Thus, the inter-vehicle distance can be all the smaller (with a minimum not to be exceeded for safety reasons) as the level of autonomy associated with the current driving mode is high and the level of confidence is high.

[0083] According to other examples, recommendations for overtaking the second vehicle 12, for changing lanes of traffic, can be made according to the determined current driving mode of the second vehicle 12.

[0084] When the first vehicle 11 has an autonomy level of 2, 3, or higher, i.e., when the first vehicle 11 is equipped with one or more ADAS systems configured to assist the driver in controlling the vehicle, then the control of the entire set of driver assistance systems of the first vehicle 11 includes the control of at least one ADAS system, for example, the ACC system or the SALC system. The control of a SALC system includes, for example, adjusting the value of a system control parameter, for example, the target 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 target inter-vehicle time parameter is, for example, adjusted downwards when the autonomy level associated with the current driving mode of the second vehicle 12 is above a threshold (for example, partially autonomous driving mode). autonomous and higher) and that the confidence level is above a threshold (e.g., above 0.8) and maintained at its default value or adjusted upwards when the autonomy level associated with the current driving mode of the second vehicle is below the threshold (e.g., manual driving mode) and / or that the confidence level is below the threshold.

[0085] According to a particular embodiment, the process further comprises a set of operations 25 according to which: - a first representative piece of information identifying a group of vehicles to which the second vehicle belongs, among a set of vehicle groups, is determined from the data obtained from the perception sensors of the first vehicle 11; and - a first level of danger of the second vehicle 12 is determined from the first information and a database associating a reference level of danger to each group of vehicles in 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.

[0086] According to this particular embodiment, the second vehicle 12 is for example identified from its registration plate obtained by image processing and / or from the make, model and / or type of the second vehicle 12 obtained by image processing via the first data.

[0087] Such initial information makes it possible to identify which group of vehicles the second vehicle 12 belongs to, a group of vehicles including, for example, vehicles of the same model of the same brand or vehicles of the same type (for example, van, utility vehicle, etc.).

[0088] The first piece of information is used to query a database (local in the first vehicle 11 or remote in the "cloud" 100) and obtain in return information representative of a level of danger, called the reference level, associated with the group to which the second vehicle 12 belongs. Such a database is, for example, updated by car manufacturers.

[0089] A hazard level (or risk level) is determined for each group of vehicles based on historical accident and / or incident data for vehicles belonging to that group, for example, according to the number of recorded incidents and / or accidents (for example, over a specific time period, such as the past 5 or 10 years). Indeed, manufacturers of autonomous or automated vehicles are required at the European level to produce reports related to the operation of autonomous or automated vehicles, and government agencies are required to establish a mandatory incident or accident reporting system. autonomous vehicles. Historical data is thus analyzed to determine, for each vehicle group, a reference level of risk.

[0090] 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.

[0091] 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 current driving mode and the associated confidence level.

[0092] According to another particular embodiment, the process further comprises a set of operations 26 according to which: - third representative data of dangerous behavior of the second vehicle 12 in environment 1 detected are determined from the data obtained from the perception sensors of the first vehicle 11; - a second piece of information representative of an occurrence of dangerous behavior is determined from the third set of data; and - a second level of danger of the second vehicle is determined from the second piece of information.

[0093] According to this other embodiment, the data acquired by the 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 the second vehicle 12 has been detected by the first vehicle 11.

[0094] Dangerous behavior corresponds, for example, to an action or maneuver by the second vehicle 12 that does not conform to a rule in a set of rules, such as, for example, the rules of the highway code.

[0095] 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 above the legal limit, - Speed ​​below a certain threshold, in relation to the legal limit, - Inappropriate stopping / parking distance in the roadway, - Distance between vehicles (or time between vehicles) below a certain threshold, - Dangerous overtaking of a vehicle or vulnerable road user (for example, a cyclist), - Crossing a solid line, - Fish tail, - Failure to yield priority, - Going through a red light, - Traffic without lights on - Defect (total or partial) of traffic lights, - Etc.

[0096] When such an event related to dangerous behavior occurs, the third data relating to this behavior is recorded in the memory of the first vehicle and / or transmitted to a remote device such as the 111 server via a wireless connection. This third data includes, for example, an identifier of the identified dangerous behavior. In one variant, the third data also includes information relating to the location (e.g., GPS coordinates), the time (e.g., date and time) when the detected dangerous event occurred, data identifying the second vehicle 12 (e.g., its license plate number), one or more images of the dangerous event, the type of event, and / or a value representing the criticality or level of danger of the dangerous behavior, etc.

[0097] The number of times a detected dangerous behavior is calculated or determined (for example, as long as the second vehicle 12 is detected by the perception sensor(s) of the first vehicle 11) from the third data points to obtain the second piece of information representing the occurrence of dangerous behaviors. This calculation is performed by a computer in the vehicle or by the remote device receiving the third data points, as applicable. This second piece of information is, for example, also stored in the memory of the first vehicle 11 or the remote device.

[0098] A second level of danger of the second vehicle is determined from the second information, the second level of danger (for example between 0 and 1) increasing as the number of occurrences increases.

[0099] When this second level of danger is determined by a computer of the first vehicle, the data representing this second level of danger are optionally transmitted to a remote device for archiving for example and / or to establish danger statistics per vehicle.

[0100] When this second level of danger is determined by the remote device, the data representing this second level of danger are transmitted to the first vehicle 11 via the wireless connection.

[0101] According to this other embodiment, the second level of danger is taken in account for the control of the on-board system(s) of the first vehicle 11 to operation 24, in addition to the current driving mode and associated confidence level, or even in addition to the first level of danger.

[0102] According to another embodiment, the process further comprises a set of operations 27 according to which: - Fourth data points, representative of a dangerous behavior report, are generated from the third data points; and - the fifth data is transmitted to a remote device such as the server 111 via a wireless connection linking the first vehicle 11 to the "cloud" 100.

[0103] These operations are implemented by one or more computers embedded in the first vehicle 11 or by a remote server-type device receiving the third data from the first vehicle 11.

[0104] The fifth data includes, for example, the type of hazardous event detected and / or information relating to the location (e.g. GPS coordinates), the time (e.g. date and time) when the hazardous event detected took place and / or data identifying the second vehicle 12 (e.g. its registration number) and / or one or more images of the hazardous event and / or a value representative of the criticality or level of danger of the hazardous behavior.

[0105] An automatic report is generated from third-party data, for example according to a document template, to be edited in a predefined format. The report is then transmitted, for example, to a device configured to store all reports generated from data obtained from vehicles traveling on roads.

[0106] Such a report responds, for example, to the recommendations of the European Commission relating to NATM (New Assessment Test Methods) which open the way to voluntary reporting for autonomous or automated vehicles in circulation.

[0107] 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 when interacting with automated vehicles.

[0108] Figure 3 schematically illustrates a device 3 configured to determine a typical driving mode of a second vehicle traveling in the vicinity of a first vehicle, for example the first vehicle 11, according to a particular and non-limiting embodiment of the present invention. The device 3 corresponds, for example, to a device embedded in the first vehicle 11, for example a computer.

[0109] According to another example, device 3 corresponds to a server or computer type data processing device.

[0110] Device 3 is, for example, configured to carry out the operations described opposite Figures 1 and 2 and / or the steps of the process described opposite [Fig. 4]. Examples of such a device 3 include, but are not limited to, embedded electronic equipment such as a vehicle's on-board computer, an electronic control unit such as an ECU (Electronic Control Unit), a smartphone, a tablet, or a laptop computer. The elements of device 3, individually or in combination, can be integrated into a single integrated circuit, into several integrated circuits, and / or into discrete components. Device 3 can be implemented in the form of electronic circuits or software (or computer) modules, or a combination of electronic circuits and software modules.

[0111] The device 3 comprises one (or more) processor(s) 30 configured to execute instructions for carrying out the steps of the process and / or for executing instructions from the software 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, for example, volatile and / or non-volatile memory, and / or includes a memory storage device that may include volatile and / or non-volatile memory, such as EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, magnetic disk, or optical disk.

[0112] The computer code of the embedded software(s) including the instructions to be loaded and executed by the processor is for example stored on memory 31.

[0113] According to various specific 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 (Telematic Control Unit), for example via a communication bus or through dedicated input / output ports.

[0114] According to a particular and non-limiting embodiment, the device 3 includes a block 32 of interface elements for communicating with external devices. The interface elements of the block 32 include one or more of the following interfaces: - Radio frequency (RF) interface, for example, Wi-Fi® (according to IEEE 802.11), for example in the 2.4 or 5 GHz frequency bands, or Bluetooth® (according to IEEE 802.15.1), in the 2.4 GHz frequency band, or Sigfox using UBN (Ultra Narrow Band) radio technology narrow), or LoRa in the 868 MHz frequency band, LTE (from the English "Long-Term Evolution" or in French "Evolution à long terme"), LTE-Advanced (or in French LTE-avancé); - 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", or in French "Réseau interconnecté local").

[0115] According to another particular and non-limiting embodiment, the device 3 includes a communication interface 33 which enables communication with other devices (such as other computers in the embedded 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), CAN FD (Controller Area Network Flexible Data-Rate), FlexRay (standardized by ISO 17458) or Ethernet (standardized by ISO / IEC 802-3) type.

[0116] According to a particular and non-limiting embodiment, the device 3 can provide output signals to one or more external devices, such as a display screen 340, touch or not, one or more speakers 350 and / or other peripherals 360 (projection system) via output interfaces 34, 35 and 36 respectively. According to a variant, one or more of the external devices is integrated into the device 3.

[0117] Figure 4 illustrates a flowchart of the various steps in a method for determining a typical driving mode of a second vehicle traveling in the vicinity of a first vehicle, for example, the first vehicle 11, according to a particular and non-limiting embodiment of the present invention. The method is implemented, for example, by a device embedded in the first vehicle 11 or by a system comprising one or more devices embedded in the first vehicle 11 and one or more remote devices such as servers connected wirelessly to the first vehicle 11.

[0118] In a first step 41, representative data of the second vehicle are obtained by the first vehicle from at least one environmental perception sensor on board the first vehicle, the data corresponding to: • initial representative data from at least one image of the second vehicle, and / or • second representative data for the detection of radiation emitted by the second vehicle.

[0119] In a second step 42, at least two indicators of the current driving mode of the second vehicle are determined by processing the data obtained in the first step 41.

[0120] In a third step 43, the current driving mode of the second vehicle and a confidence index associated with the current driving mode are determined from at least two indicators.

[0121] According to one variant, the variants and examples of the operations described in relation to one of Figures 1 and 2 apply to the steps of the process in [Fig.4].

[0122] Of course, the present invention is not limited to the 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 departing from the scope of the present invention. The same would apply to a device configured for implementing such a method.

[0123] The present invention also relates to a vehicle, for example an automobile or more generally an autonomous land-powered vehicle, comprising the device 3 of [Fig.3] or a system comprising the first vehicle and one or more remote devices connected by wireless communication to the first vehicle.

Claims

Claims

1. Method for determining a current driving mode 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 sensor for perceiving said environment on board said first vehicle (11), said data comprising: • first data representative of at least one image of said second vehicle (12), and / or • second data representative of detection of radiation emitted by said second vehicle; - determining (22, 42), by processing said data, at least two indicators of the current driving mode of said second vehicle (12); - determining (23, 43) the current driving mode of the second vehicle (12) and a confidence index associated with the current driving mode determined from said at least two indicators.

2. Method according to claim 1, for which said at least two indicators belong to a set of indicators comprising: - a presence of a determined light indicator on said second vehicle; - an absence of a person in a driving position of said second vehicle; - a presence of laser radiation emitted during a circulation phase of said second vehicle; and - a presence of millimeter wave radiation emitted during the circulation phase of said second vehicle.

3. Method according to claim 1 or 2, for which said determination of the current driving mode comprises a classification of said current driving mode in a class belonging to a set of classes comprising: - a first class representative of a semi-autonomous driving mode; - a second class representative of a dual-mode fully autonomous driving mode; and - a third class representative of a dual-mode driving mode completely autonomous non-dual mode.

4. Method according to one of claims 1 to 3, 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 current driving mode of the second vehicle and said associated confidence index.

5. Method according to one of claims 1 to 4, further comprising the following steps (25): - determining a first 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 data; - determining a first level of danger of said second vehicle (12) from said first 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.

6. Method according to one of claims 1 to 5, further comprising the following steps (26): - determination of third data representative of dangerous behaviors of said second vehicle (12) in said environment detected from said data; - determination of second information representative of an occurrence of said dangerous behaviors from said third data; - determination of a second level of danger of said second vehicle (12) from said second information.

7. Method according to claims 4 to 6, 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.

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 current driving mode 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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