Method and device for controlling an adaptive speed regulation system of a vehicle based on road surface conditions

Abstract

The present invention relates to a method and device for controlling an adaptive cruise control system, referred to as an ACC system, of a first vehicle (10) following a second vehicle (11) corresponding to a target vehicle of the ACC system. Initial data representing the speed of the first vehicle are received, and a first target distance between the first and second vehicles is determined based on this initial data. Second data representing the grip conditions of the first vehicle are also received, and a correction factor for the first target distance is determined based on this second data. A second target distance is then determined based on the first distance and the correction factor, and the ACC system is controlled according to this second target distance. Figure 1 (for the abstract)

Description

Title of the invention: Method and device for controlling an adaptive speed regulation system of a vehicle based on traction conditions technical field

[0001] The present invention relates to methods and devices for controlling an adaptive speed regulation system of a vehicle, in particular a motor vehicle. The present invention also relates to a method and device for regulating the speed of a vehicle. The present invention also relates to a method and device for controlling a vehicle, in particular an autonomous vehicle. Technological background

[0002] Some contemporary vehicles are equipped with functions or system(s) or driving assistance, called AD AS (from the English "Advanced Driver-Assistance System" or in French "Système d'aide à la conduite avancé").

[0003] Among these systems, the adaptive cruise control system, or ACC, has as its primary function the automatic and adaptive regulation of the speed of the vehicles equipped with it, according to their environment. Such an ACC system determines one or more acceleration and / or braking commands based on a speed command and information relating to the vehicle's environment, the acceleration and / or braking command(s) being specific to regulating the vehicle's speed adaptively, that is to say, by taking into account the vehicle's environment.

[0004] This environmental information corresponds, for example, to the distance between the vehicle equipped with the ACC system and a vehicle traveling in front of it, the speed (e.g., relative speed) of the vehicle in front, the acceleration (or deceleration) of the vehicle in front, and / or a regulatory speed limit. Such a vehicle is called the target vehicle or target object of the ACC system. The acceleration command(s) are, for example, determined from a control law based on estimates of the torque supplied by a powertrain (e.g., an internal combustion or electric motor) to one or more wheels of the vehicle and the vehicle's current acceleration.

[0005] Environmental information about a vehicle is obtained, for example, from sensors on board the vehicle, such as radar. This information is particularly important for a vehicle, for example, to improve vehicle safety by taking into account the surrounding environment, including other vehicles.

[0006] A target distance separating the two vehicles is determined in order to ensure, in particular, the safety of the vehicle occupants. This distance allows the vehicle equipped with the ACC system to brake and stop without colliding with the target vehicle in front of it. Setting such a target distance is an important safety criterion. Summary of the present invention

[0007] One object of the present invention is to solve at least one of the problems of the technological background described above.

[0008] Another object of the present invention is to improve the operation of an ACC system of a vehicle.

[0009] Another object of the invention is to improve the determination of a target distance ensuring the safety of the vehicle and its passengers.

[0010] According to a first aspect, the present invention relates to a method for controlling an adaptive speed regulation system, referred to as an ACC system, of a first vehicle following a second vehicle corresponding to a target vehicle of the ACC system, the method comprising the following steps: - receipt of initial data representative of the speed of the first vehicle; - determination of an initial target distance between the first vehicle and the second vehicle based on the initial data; - receipt of second data representative of the adhesion conditions of the first vehicle; - determination of a correction coefficient for the first target distance based on the second set of data; - determination of a second target distance as a function of the first target distance and the correction coefficient; - control of the ACC system according to the second target distance.

[0011] The method thus makes it possible to determine a target distance between the first vehicle equipped with the ACC system and the target vehicle based on the speed of the first vehicle as well as the first vehicle's road grip conditions. The target distance thus determined is adapted to the actual conditions in which the first vehicle is traveling.

[0012] According to one variant of the method, the second set of data comprises: - data representative of an activation state of a windshield wiper system fitted to the first vehicle, and - representative data of wheel slippage of at least one wheel of the first vehicle.

[0013] This second data makes it possible to estimate the level of adhesion of the first vehicle to a road on which it is traveling.

[0014] According to another variant, the method further includes a step of receiving third data representative of an adjustable weighting factor, the second target distance being further determined as a function of the adjustable weighting factor.

[0015] A user is thus able to adapt the distance separating the first vehicle from the target vehicle.

[0016] According to yet another variant of the process, the correction coefficient is between 1 and 1.5.

[0017] Applying a correction factor of 1 is equivalent to not correcting the first speed. A factor of 1.5 is commonly used to correct a braking distance in wet weather compared to a braking distance on dry pavement.

[0018] According to an additional variant of the method, the correction coefficient is equal to 1 when the speed of the first vehicle is less than a threshold value.

[0019] The second distance is then equal to the first distance when the speed is less than the threshold value.

[0020] According to another variant, the method further includes a step of receiving fourth data representative of driving conditions of the first vehicle, the correction coefficient being further determined according to the fourth data.

[0021] Taking into account driving conditions makes it possible to refine the correction of the distance separating the two vehicles.

[0022] According to yet another variant of the method, the first target distance is determined as a function of a stopping distance called Da determined by: Da = ax V + V2 / (2 x G xa ), with: - V, the speed of the first vehicle, - has a coefficient representing the reaction time of an onboard system of the first vehicle, - G is a coefficient of gravity, and - has a coefficient representing the level of adhesion of the first vehicle on a road.

[0023] This mathematical formula allows the braking distance of a vehicle to be precisely defined.

[0024] According to a second aspect, the present invention relates to a control device for a vehicle adaptive speed regulation system, 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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

[0032] 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 3, in which:

[0033] [Fig-1] schematically illustrates a vehicle environment, according to an example of particular and non-limiting implementation of the present invention;

[0034] [Fig.2] schematically illustrates a device configured to control an adaptive speed regulation system of the first vehicle of the [Fig.1], according to a particular and non-limiting embodiment of the present invention;

[0035] [Fig.3] illustrates a flowchart of the different stages of a control method for an adaptive speed regulation system of the first vehicle of [Fig.1], according to a particular and non-limiting embodiment of the present invention. Description of examples of achievements

[0036] A method and a control device for an adaptive speed regulation system of a vehicle will now be described in what follows with joint reference to Figures 1 to 3. The same elements are identified with the same reference signs throughout the description that follows.

[0037] 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.

[0038] According to a particular and non-limiting embodiment of the present invention, the control of an adaptive speed regulation system, called ACC system, of a first vehicle following a second vehicle corresponding to a target vehicle of the ACC system includes the reception of first data representative of a speed of the first vehicle and the determination of a first target distance between the first vehicle and the second vehicle as a function of the first data.

[0039] Second data representing the adhesion conditions of the first vehicle are also received and a correction coefficient for the first target distance is determined based on the second data.

[0040] A second target distance is then determined based on the first distance and the correction factor, and the ACC system is controlled based on the second target distance.

[0041] Such control of the distance separating the first vehicle from the target vehicle makes it possible to adapt this distance to the road surface conditions. In the event of braking by the target vehicle, the first vehicle is then able to stop without risk of colliding with the target vehicle, regardless of the road surface conditions.

[0042] Fig. 1 illustrates a first vehicle 10, for example a motor vehicle, travelling on a portion of road in environment 1. According to other examples, the first vehicle 10 corresponds to a coach, a bus, a truck, a utility vehicle or a motorcycle, that is to say a motorized land vehicle.

[0043] The first vehicle 10 corresponds to a vehicle operating under the full supervision of a driver or operating in an autonomous or semi-autonomous mode. The first vehicle 10 operates at an autonomy level of 0 or at an autonomy level ranging from 1 to 5, for example, according to the scale defined by the US federal agency which has established 5 levels of autonomy ranging from 1 to 5, level 0 corresponding to a vehicle with no autonomy, whose driving is under the total supervision of the driver, level 1 corresponding to a vehicle with a minimal level of autonomy, whose driving is under the supervision of the driver with minimal assistance from an AD AS system, and level 5 corresponding to a fully autonomous vehicle.

[0044] The 5 levels of autonomy in the classification of the federal agency responsible for road safety are: - level 0: no automation, the vehicle driver fully controls the main functions of the vehicle (engine, accelerator, steering, brakes); - 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.

[0045] According to a particular embodiment, the first vehicle 10 operates in a semi-autonomous or autonomous mode, that is to say with a level of autonomy greater than or equal to 2 according to the classification above.

[0046] According to the example in [Fig.1], the first vehicle 10 travels on a section of road with two traffic lanes 1001, 1002. The first vehicle 10 travels for example on the right traffic lane 1001.

[0047] The concepts of right and left are defined according to the direction of travel of the first vehicle 10. The example in [Fig. 1] corresponds to an example in which the Vehicles travel on the right, as in France. However, the invention is not limited to such an example and extends to all road configurations, including those where vehicles travel on the left.

[0048] According to the example in [Fig.1], the first vehicle 10 follows a second vehicle 11, at a distance d, the second vehicle 11 traveling on the same traffic lane 1001 as the first vehicle 10 and in the same direction as the first vehicle 10.

[0049] The second vehicle 11 corresponds to the target object, also called the target vehicle, selected by the ACC system of the first vehicle 10.

[0050] The first vehicle 10 carries, for example, one or more of the following sensors: - one or more millimeter wave radars arranged on the first vehicle 10, 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 example the second vehicle 11 located in front of the first vehicle 10 according to the example in [Fig. 1]), in order to detect obstacles and their distances from the first vehicle 10;and / or - one or more LIDAR(s) (Light Detection and Ranging), a LIDAR sensor corresponding to an optoelectronic system composed of a laser emitter, a receiver comprising a light collector (to collect the portion 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 (for example the second vehicle 11) 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 10 located in the field of vision of the camera(s).

[0051] The data obtained from this or these sensors vary depending on the type of sensor. In the case of radar or LiDAR, the data corresponds, for example, to distance data between points on the detected object and the sensor. Each detected object is thus represented by a point cloud (each point corresponding to a point on the object receiving the radiation emitted by the sensor and reflecting at least part of this radiation), the point cloud representing the envelope (or part of the envelope) of the detected object as seen by the sensor and ultimately by the first vehicle 10 carrying the sensor. In the case of a video camera, the data corresponds to data associated with each pixel of the acquired image(s), for example, grayscale values ​​coded on, for example, 8, 10, 12 or more bits for each color channel, for example RGB (Red, Green, Blue or in French "Red, green, blue"). This data allows, for example, to determine the successive positions taken by an object moving in environment 1, for example the second vehicle 11, and to deduce one or more dynamic parameters of the moving object such as position, speed and / or acceleration. This data also makes it possible to determine the lines on the ground to, for example, help determine whether the second vehicle 11 and the first vehicle 10 belong to the same traffic lane.

[0052] The data acquired by the on-board sensor(s) feed, for example, one or more driver assistance systems, called AD AS (from the English "Advanced Driver-Assistance System" or in French "Système d'aide à la conduite avancé"), on-board in the first vehicle 10. Such an AD AS system is configured to assist, or even replace, the driver of the first vehicle 10 in controlling the first vehicle 10 on its journey.

[0053] The first vehicle 10 includes in particular an AD AS system corresponding to an automatic speed regulation system, known as the ACC system.

[0054] A control process of the ACC system of the first vehicle 10 whose target vehicle is the second vehicle 11 is advantageously implemented by the first vehicle 10, i.e. by a computer or a combination of computers of the embedded system of the first vehicle 10, for example by the computer or computers in charge of controlling the ACC system.

[0055] A distance between the first vehicle 10 and the second vehicle 11 constitutes a setpoint provided to the ACC system; this distance is commonly called the inter-vehicle distance (IVD). According to one variant, the setpoint is an inter-vehicle time; nevertheless, this setpoint is equivalent to the IDD setpoint, the speed of the first vehicle 10 being the proportionality coefficient between these two setpoints.

[0056] In a first operation, initial data representing the speed of the first vehicle 10 are received.

[0057] These data are received for example from one or more sensors 101, via one or more communication buses of the on-board system of the first vehicle 10, for example a communication bus of the type 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), Ethernet (according to the ISO / IEC 802-3 standard) or LIN (from the English "Local Interconnect Network" or in French "Réseau interconnecté local").

[0058] A sensor 101 belongs, for example, to a set of sensors comprising: - a radar, - a LIDAR, and - a camera.

[0059] In a second operation, a first target distance is determined between the first vehicle 10 and the second vehicle 11 based on the first data.

[0060] A stopping distance, called Da, is the sum of a distance traveled before braking of the first vehicle 10, called reaction distance and called Dr, and a braking distance of the first vehicle, called Df.

[0061] The reaction distance Dr is due to the reaction time or information processing time that causes the braking, either a reaction time of the driver of the first vehicle 10 or an information processing time by an on-board system of the first vehicle 10 controlling the braking of the first vehicle 10. The reaction distance Dr is then proportional to the speed of movement of the first vehicle 10 and corresponds to the distance traveled by the first vehicle 10 before activating its braking.

[0062] Thus, this reaction distance Dr is defined by:

[0063] Dr = ax V, with: - V the speed of the first vehicle (10), - has a coefficient representative of a reaction time of an on-board system of the first vehicle (10).

[0064] The braking distance Df is defined as a function of the speed V of the first vehicle and data related to the adhesion of the first vehicle 10. In the absence of slippage, the braking distance Df is, for example, defined by:

[0065] Df = V2 / (2 x G xa), with: - V the speed of the first vehicle (10), - G is a coefficient of gravity, and - has a coefficient representing a level of adhesion of the first vehicle 10 on a road.

[0066] The gravitational coefficient G corresponds to the normal value of the acceleration due to Earth's gravity and is approximately 9.81 m / s²

[0067] The coefficient a is defined for a given vehicle as a function of its mass, the grip of its tires and the surface on which it travels, for example on asphalt.

[0068] According to a first particular embodiment, the first target distance is determined as a function of a first stopping distance Da determined by:

[0069] Da = ax V + V2 / (2 x G xa), with: - V the speed of the first vehicle (10), - has a coefficient representing the reaction time of an on-board system of the first vehicle (10), - G is a coefficient of gravity, and - has a coefficient representing a level of adhesion of the first vehicle (10) on a road.

[0070] According to a second particular embodiment, the first target distance is determined as a function of a second stopping distance Da' being determined in meters as the square of the tens digit of the speed V of the first vehicle 10.

[0071] Thus, if the first vehicle is traveling at 80 km / h, the second stopping distance is determined by:

[0072] Da'(80km / h) = 8x8 = 64m.

[0073] Similarly, if the first vehicle is traveling at 130 km / h, the second stopping distance is determined by:

[0074] Da' (130km / h) =13x13=169m.

[0075] It should be noted that if the speed is defined in another unit, for example in miles / hour (mph), this calculation is only valid if the latter is converted into the unit km / h.

[0076] This second formulation of the stopping distance is a simplified version but is, however, relatively accurate.

[0077] Thus, the first target distance is, for example, determined based on a stopping distance determined from the speed V of the first vehicle. It is, for example, equal to or proportional to this stopping distance.

[0078] In a third operation, second data representative of adhesion conditions of the first vehicle 10 are received.

[0079] These second data include, for example: - representative data of the activation state of a windshield wiper system fitted to the first vehicle 10, and - representative data of wheel slippage of at least one wheel of the first vehicle 10.

[0080] A windshield wiper system of a first vehicle 10 is activated in particular in rainy weather. The control unit implementing the process receives, for example, information relating to the frequency of activation of the windshield wiper system or information relating to the amount of water present on a window provided by a rain sensor of the windshield wiper system.

[0081] Data representative of wheel slippage are received for example from a sensor present at the level of a wheel or received from a system such as an ABS system (from the German "Antiblockiersystem", in French anti-lock braking system) or ESP (from the English "Electronic Stability Program", in French "electronic trajectory corrector").

[0082] According to a particular embodiment, the data representing the slippage of at least one wheel

[0083] In a fourth operation, a correction coefficient for the first target distance is determined as a function of the second data.

[0084] The correction coefficient is for example between 1 and 1.5.

[0085] According to one variant, the correction coefficient is between 1 and 2.

[0086] The value of 1 is assigned, for example, to the correction coefficient when the windshield wiper system is inactive and when no wheel slippage has been detected. This data reflects optimal grip conditions in near-dry weather.

[0087] Conversely, if, for example, according to the second set of data, several wheels have slipped and a windshield wiper system is active, then the grip conditions appear poor. A value of 1.5 is assigned, for example, to the correction factor. Indeed, it is common practice to multiply a stopping distance by 1.5 when a road is wet.

[0088] According to one embodiment, if a windshield wiper system is active and several wheels are slipping very frequently, then the grip conditions appear extremely poor. A value of 2 is assigned, for example, to the correction factor. Indeed, in this type of condition, a braking distance that is part of the stopping distance is commonly doubled.

[0089] According to a particular embodiment, the correction coefficient is equal to 1 when the speed of the first vehicle 10 is less than a threshold value.

[0090] A threshold value corresponds for example to a speed of 30km / h or 45km / h.

[0091] For example, if the first vehicle 10 is traveling at a speed of less than 30km / h, the correction coefficient is equal to 1.

[0092] According to another particular embodiment, in a fifth operation, fourth data representing the driving conditions of the first vehicle 10 are received.

[0093] Such data correspond, for example, to: - an analysis of the road, its curves, incline, and type of surface, - meteorological information, and / or - a measurement of a humidity level.

[0094] For example, the fourth data points are representative of the presence of a puddle on the 1001 taxiway which could generate aquaplaning, or the weather information determines a risk of snow or ice.

[0095] According to this particular embodiment, the correction coefficient is further determined as a function of the fourth data.

[0096] In a sixth operation, a second target distance is determined as a function of the first distance and the correction coefficient.

[0097] The second target distance is for example equal to the product of the first target distance and the correction coefficient.

[0098] For example, if the correction coefficient is equal to 1.5, then the second target distance is equal to 1.5 times the first target distance, i.e. an increase of 50% of the first target distance.

[0099] According to a particular embodiment, in a seventh operation, third data representing an adjustable weighting factor are received.

[0100] These third data allow, for example, a user to configure and personalize the determination of the second target distance.

[0101] For example, a user is able to increase the second target distance when he judges the adhesion conditions to be unfavorable, or conversely decrease the second target distance when he judges the adhesion conditions to be favorable.

[0102] These third data are for example received from a Human-Machine Interface, called HMI, embedded in the first vehicle 10.

[0103] The second target distance is then, in addition, determined according to the adjustable weighting factor.

[0104] For example, the second target distance is proportional to the first target distance, the slope, and the adjustable weighting factor.

[0105] In an eighth operation, the ACC system is controlled according to the second target distance.

[0106] The ACC system thus receives the second target distance as its setpoint. When grip conditions are poor, for example, when there is a risk of skidding during braking, which increases the stopping distance of the first vehicle 10, the DIV (Distance of Injury) is then defined according to these adverse grip conditions. The DIV is thus increased, and the safety level of the passengers of the first vehicle 10 is therefore improved.

[0107] In the case where the second target distance is greater than a previously determined target distance or the current distance d, the deceleration of the first vehicle 10 is for example progressive in order to preserve the comfort of the passengers of the first vehicle 10 or to avoid any risk of activation of an anti-slip system following too abrupt a deceleration.

[0108] Figure 2 schematically illustrates a device 2 configured to control a SALC system, according to a particular and non-limiting embodiment of the present invention. The device 2 corresponds, for example, to a device embedded in the first vehicle 10, for example a computer.

[0109] Device 2 is, for example, configured to carry out the operations described opposite [Fig. 1] and / or the steps of the process described opposite [Fig. 3]. Examples of such a device 2 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 2, individually or in combination, can be integrated into a single integrated circuit, into several integrated circuits, and / or into discrete components. Device 2 can be implemented in the form of electronic circuits or software (or computer) modules, or a combination of electronic circuits and software modules.

[0110] The device 2 comprises one (or more) processor(s) 20 configured to execute instructions for carrying out the steps of the process and / or for executing instructions from the software embedded in the device 2. The processor 20 may include integrated memory, an input / output interface, and various circuits known to those skilled in the art. The device 2 further comprises at least one memory 21, 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.

[0111] 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 21.

[0112] According to various particular and non-limiting embodiments, the device 2 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.

[0113] According to a particular and non-limiting embodiment, the device 2 includes a block 22 of interface elements for communicating with external devices, for example a remote server or the cloud, or the first vehicle 10 when the device 2 corresponds to a smartphone or tablet, for example. The interface elements of the block 22 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).

[0114] According to another particular and non-limiting embodiment, the device 2 includes a communication interface 23 which enables communication with other devices (such as other computers in the embedded system or embedded sensors) via a communication channel 230. The communication interface 23 corresponds, for example, to a transmitter configured to transmit and receive information and / or data via the communication channel 230.Communication interface 23 corresponds, for example, to a wired network of the type CAN (Controller Area Network), CAN FD (Controller Area Network Flexible Data-Rate), FlexRay (standardized by ISO 17458), Ethernet (standardized by ISO / IEC 802-3) or LIN (Local Interconnect Network).

[0115] According to a particular and non-limiting embodiment, the device 2 can provide output signals to one or more external devices, such as a display screen, touch-sensitive or not, one or more loudspeakers and / or other peripherals (projection system) via respective output interfaces. In one variant, one or more of the external devices is integrated into the device 2.

[0116] Figure 3 illustrates a flowchart of the different steps of a method 3 for controlling an ACC system of a vehicle, for example of the first vehicle 10, 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 10 or by the device 2 of Figure 2.

[0117] In a first step 31, initial data representing the speed of the first vehicle 10 are received.

[0118] In a second step 32, a first target distance between the first vehicle 10 and the second vehicle 11 is determined based on the first data.

[0119] In a third step 33, second data representative of adhesion conditions of the first vehicle 10 are received.

[0120] In a fourth step 34, a correction coefficient for the first target distance is determined as a function of the second data.

[0121] In a fifth step 35, a second target distance is determined as a function of the first target distance and the correction coefficient

[0122] In a sixth step 36, the ACC system is controlled according to the second target distance.

[0123] According to one variant, the variants and examples of the operations described in relation to [Fig.1] apply to the steps of the process in [Fig.3].

[0124] Of course, the present invention is not limited to the embodiments described above but extends to a method for controlling a vehicle, for example an autonomous vehicle, which would include secondary steps without falling 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 an adaptive speed control system for vehicles comprising device 2 of [Fig.2].

[0126] The present invention also relates to a vehicle, for example an automobile or more generally an autonomous land-based motor vehicle, comprising the device 2 of [Fig.2] or the adaptive speed control system for vehicles above.

Claims

Demands

1. A method for controlling an adaptive speed regulation system, referred to as an ACC system, of a first vehicle (10) following a second vehicle (11) corresponding to a target vehicle of said ACC system, said method comprising the following steps: - receiving (31) first data representing a speed of said first vehicle (10); - determining (32) a first target distance between the first vehicle (10) and the second vehicle (11) as a function of the first data; - receiving (33) second data representing the grip conditions of said first vehicle (10); - receiving third data representing an adjustable weighting factor; - determining (34) a correction coefficient for said first target distance as a function of said second data;- determination (35) of a second target distance as a function of said first target distance, said correction coefficient and said adjustable weighting factor; - control (36) of said ACC system as a function of said second target distance.;

2. A method according to claim 1, wherein said second data comprise: - data representing an activation state of a windshield wiper system equipping the first vehicle (10), and - data representing a slippage of at least one wheel of the first vehicle (10).

3. A method according to any one of claims 1 to 2, wherein said correction coefficient is between 1 and 1.

5.

4. A method according to any one of claims 1 to 3, wherein said correction coefficient is equal to 1 when said speed of the first vehicle (10) is less than a threshold value.

5. A method according to any one of claims 1 to 4, further comprising a step of receiving fourth data representative of driving conditions of the first vehicle (10), said correction coefficient being further determined as a function of said fourth data.

6. A method according to any one of claims 1 to 5, wherein said first target distance is determined as a function of a stopping distance said Da determined by: Da = ax V + V2 / (2 x G xa ), with: - V the speed of the first vehicle (10), - a a coefficient representing a reaction time of an on-board system of the first vehicle (10), - G a coefficient of gravity, and - a a coefficient representing a level of adhesion of the first vehicle (10) on a road.

7. A computer program comprising instructions for carrying out the method according to any one of the preceding claims, when such instructions are executed by a processor.

8. Device (2) for controlling a vehicle adaptive speed regulation system, said device (2) comprising a memory (21) associated with at least one processor (20) configured for carrying out the steps of the method according to any one of claims 1 to 6.

9. Vehicle comprising the device (2) according to claim 8.

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