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 grip conditions Technical field

[0001] The present invention relates to methods and devices for controlling an adaptive speed control system of a vehicle, in particular a motor vehicle. The present invention also relates to a method and a device for regulating the speed of a vehicle. The present invention also relates to a method and a 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, known as AD AS (from the English “Advanced Driver-Assistance System” or in French “Advanced Driving Assistance System”).

[0003] Among these systems, the adaptive cruise control system, known as ACC (from the English "Adaptive Cruise Control"), has as its primary function the automatic regulation, in an adaptive manner, of the speed of the vehicles equipped therewith according to their environment. Such an ACC system determines one or more acceleration and / or braking instructions according to a speed instruction and information relating to the environment of the vehicle, the acceleration and / or braking instruction(s) being capable of regulating the speed of the vehicle in an adaptive manner, that is to say by taking into account the environment of the vehicle.

[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, to the speed (for example relative) of the vehicle traveling in front, to the acceleration (or deceleration) of the vehicle traveling in front and / or to a regulatory speed limit. Such a vehicle is called a target vehicle or target object of the ACC system. The acceleration instruction(s) are, for example, determined from a control law based on estimates of the torque supplied by a powertrain (for example a thermal or electric engine) to one or more wheels of the vehicle and the current acceleration of the vehicle.

[0005] The environmental information of a vehicle is for example obtained from sensors on board the vehicle, such as radars for example. This information is particularly important for a vehicle, for example to improve the safety of the vehicle by taking into account the environment which surrounds it, in particular other vehicles.

[0006] A target distance separating the two vehicles is determined in order to guarantee the safety of the passengers of the vehicles, this distance allowing 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] An 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 cruise control system, called 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: - reception of first data representative of a speed of the first vehicle; - determining a first target distance between the first vehicle and the second vehicle based on the first data; - reception of second data representative of grip conditions of the first vehicle; - determination of a correction coefficient for the first target distance based on the second data; - determination of a second target distance based on the first target distance and the correction coefficient; - ACC system control based on 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 as a function of the speed of the first vehicle but also as a function of the grip conditions of the first vehicle. The target distance thus determined is adapted to the actual conditions in which the first vehicle is traveling.

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

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

[0014] According to another variant, the method further comprises 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 another variant of the method, the correction coefficient is between 1 and 1.5.

[0017] Applying a correction coefficient equal to 1 amounts to not correcting first gear. A coefficient equal to 1.5 is commonly used to correct a braking distance in wet weather compared to a braking distance on dry ground.

[0018] According to a variant of the additional method, the correction coefficient is equal to 1 when the speed of the first vehicle is lower 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 comprises a step of receiving fourth data representative of driving conditions of the first vehicle, the correction coefficient being further determined as a function of 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 representative of a reaction time of an on-board system of the first vehicle, - G a coefficient of gravity, and - has a coefficient representative of the level of grip of the first vehicle on a road.

[0023] This mathematical formula makes it possible to precisely define the braking distance of a vehicle.

[0024] According to a second aspect, the present invention relates to a device for controlling an adaptive vehicle speed regulation system, the device comprising a memory associated with a processor configured for implementing the steps of the method according to the first aspect of the present invention.

[0025] According to a third aspect, the present invention relates to a vehicle, for example of 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 comprises instructions adapted for executing the steps of the method according to the first aspect of the present invention, in particular when the computer program is executed by at least one processor.

[0027] Such a computer program may use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form.

[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 method according to the first aspect of the present invention.

[0029] On the one hand, the recording medium may be any entity or device capable of storing the program. For example, the medium may comprise a storage means, such as a ROM memory, a CD-ROM or a microelectronic circuit type ROM memory, or a magnetic recording means or a hard disk.

[0030] Furthermore, this recording medium may also be a transmissible medium such as an electrical or optical signal, such a signal being able to be conveyed via an electrical or optical cable, by conventional or hertzian radio or by self-directed laser beam or by other means. The computer program according to the present invention may in particular be downloaded from an Internet-type network.

[0031] Alternatively, the recording medium may be an integrated circuit in which the computer program is incorporated, the integrated circuit being adapted to perform or to be used in performing the method in question. Brief description of the figures

[0032] Other characteristics and advantages of the present invention will emerge from the description of the particular and non-limiting exemplary embodiments of the present invention below, with reference to the appended figures 1 to 3, in which:

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

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

[0035] [Fig.3] illustrates a flowchart of the different stages of a control process of a adaptive cruise control system of the first vehicle of [Fig.l], according to a particular and non-limiting exemplary embodiment of the present invention. Description of examples of implementation

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

[0037] The terms "first(s)", "second(s)" (or "first(s)", "second(s)"), etc. are used in this document by arbitrary convention to enable different elements (such as operations, means, etc.) implemented in the embodiments described below to be identified and distinguished. Such elements may be distinct or correspond to a single element, depending on the embodiment.

[0038] According to a particular and non-limiting example of embodiment of the present invention, the control of an adaptive cruise control system, called ACC system, of a first vehicle following a second vehicle corresponding to a target vehicle of the ACC system comprises 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 representative of grip conditions of the first vehicle are also received and a correction coefficient of the first target distance is determined based on the second data.

[0040] A second target distance is then determined as a function of the first distance and the correction coefficient and the ACC system is controlled as a function of 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 grip conditions. In the event of braking of the target vehicle, the first vehicle is then able to stop without risk of colliding with the target vehicle whatever the grip conditions.

[0042] [Fig.l] illustrates a first vehicle 10, for example a motor vehicle, traveling on a portion of road in the 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 vehicle of the motorized land vehicle type.

[0043] The first vehicle 10 corresponds to a vehicle traveling under the total supervision of a driver or traveling in an autonomous or semi-autonomous mode. The first vehicle 10 travels according to a level of autonomy equal to 0 or according to a level of autonomy ranging from 1 to 5 for example, 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 su full driver perception, level 1 corresponding to a vehicle with a minimal level of autonomy, the driving of which is under the supervision of the driver with minimal assistance from an AD AS system, and level 5 corresponding to a completely autonomous vehicle.

[0044] The 5 levels of autonomy of the classification of the federal agency responsible for road safety are: - level 0: no automation, the vehicle driver has full control over 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 the vehicle's driving; cruise control is part of this level, as are other aids such as ABS (anti-lock braking system) or ESP (programmed electro-stabilizer); - level 2: automation of combined functions, the control of at least two main functions is combined in the automation to replace the driver in certain situations; for example, adaptive cruise control combined with lane centering allows a vehicle to be classified as level 2, as does automatic parking assistance (from the English “Park assist”); - level 3: limited autonomous driving, the driver can cede complete control of the vehicle to the automated system which will then be in charge of critical safety functions; autonomous driving can however only take place in certain specific environmental and traffic conditions (only on motorways for example); - level 4: fully autonomous driving under certain conditions, the vehicle is designed to ensure all critical safety functions on its own over a complete journey; the driver provides a destination or navigation instructions but is not required to make himself available to take back control of the vehicle; - level 5: completely autonomous driving without driver assistance in all circumstances.

[0045] According to a particular embodiment, the first vehicle 10 travels 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 of [Fig.l], the first vehicle 10 travels on a portion of road with two traffic lanes 1001, 1002. The first vehicle 10 travels for example on the right traffic lane 1001.

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

[0048] According to the example of [Fig.l], 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 target vehicle, selected by the ACC system of the first vehicle 10.

[0050] The first vehicle 10 for example carries 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 of [Fig.l]), with the aim of detecting obstacles and their distances from the first vehicle 10; and / or - one or more LIDAR(s) (from the English “Light Detection And Ranging”, or “Light Detection and Distance Estimation” in French), a LIDAR sensor corresponding to an optoelectronic system composed of a laser emitting device, a receiving device comprising a light collector (to collect the part of the light radiation emitted by the emitter and reflected by any object located in the path of the light rays emitted by the emitter) and a photodetector which transforms the collected light into an electrical signal; a LIDAR sensor thus makes it possible to detect the presence of objects (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 acquiring 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 according to the type of sensor. When it is a radar or a LIDAR, the data correspond for example to distance data between points of the detected object and the sensor. Each detected object is thus represented by a point cloud (each point corresponding to a point of 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. When it is a video camera, the data correspond to data associated with each pixel of the acquired image(s), for example gray level values ​​coded on for example 8, 10, 12 or more bits for each color channel, for example RGB (from the English "Red, Green, Blue" or in French: "Red, green, blue"). This data makes it possible, for example, to determine the successive positions taken by an object moving in the environment 1, for example the second vehicle 11, and to deduce one or more dynamic parameters of the moving object such as the position, speed and / or acceleration. This data also makes it possible to determine the lines on the ground, for example to participate in determining whether the second vehicle 11 and the first vehicle 10 belong to the same traffic lane, for example.

[0052] The data acquired by the on-board sensor(s) feed, for example, one or more driving assistance systems, known as AD AS (from the English “Advanced Driver-Assistance System” or in French “Advanced Driving Assistance System”) on board the first vehicle 10. Such an AD AS system is configured to assist, or even replace, the driver of the first vehicle 10 to control the first vehicle 10 on its route.

[0053] The first vehicle 10 notably incorporates an AD AS system corresponding to an automatic speed regulation system, called an ACC system.

[0054] A process for controlling the ACC system of the first vehicle 10 having the second vehicle 11 as the target vehicle is advantageously implemented by the first vehicle 10, that is to say by a computer or a combination of computers of the on-board system of the first vehicle 10, for example by the computer(s) responsible for 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 being commonly called inter-vehicle distance (IVD). According to a variant, the setpoint is an inter-vehicle time, nevertheless this setpoint is equivalent to the IVD setpoint, the speed of the first vehicle 10 being the coefficient of proportionality between these two setspoints.

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

[0057] These data are for example received 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 CAN (Controller Area Network) type, CAN FD (Controller Area Network Flexible Data-Rate), FlexRay (according to the ISO 17458 standard), Ethernet (according to the ISO / IEC 802-3 standard) or LIN (Local Interconnect Network) type.

[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 processing time of the information at the origin of the braking, either a reaction time of the driver of the first vehicle 10 or a processing time of the information 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 relating to the grip 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 a coefficient of gravity, and - has a coefficient representative of a level of adhesion of the first vehicle 10 on a road.

[0066] The coefficient of gravity G corresponds to the normal value of acceleration of terrestrial gravity and is approximately 9.81m / 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 is traveling, for example on a tarmac.

[0068] According to a first particular exemplary 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 representative of a reaction time of an on-board system of the first vehicle (10), - G a coefficient of gravity, and - has a coefficient representative of a level of grip of the first vehicle (10) on a road.

[0070] According to a second particular exemplary 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 number of tens of the speed V of the first vehicle 10.

[0071] Thus, if the first vehicle is traveling at 80km / 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 as a function of a stopping distance determined from the speed V of the first vehicle. It is for example equal or proportional to this stopping distance.

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

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

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

[0081] Data representative of the slippage of a wheel are for example received from a sensor present at the level of a wheel or received from a system such as an ABS system (from the German “Antiblockiersystem”) or ESP (from the English “Electronic Stability Program”).

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

[0083] In a fourth operation, a correction coefficient of the first target distance is determined based on 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 for example assigned to the correction coefficient when the windscreen wiper system is inactive and when no wheel slippage has been identified. These data reflect optimal grip conditions in near-dry weather.

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

[0088] According to a variant, if a windscreen wiper system is active and several wheels slip very frequently, then the grip conditions appear to be extremely poor. The value of 2 is for example assigned to the correction coefficient. Indeed, in this type of condition, a braking distance forming 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 lower 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 travels at a speed of less than 30 km / h, the correction coefficient is equal to 1.

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

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

[0094] For example, the fourth data is representative of the presence of a puddle of water on the taxiway 1001 which could generate aquaplaning, or the meteorological 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 based on 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 representative of 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 grip conditions to be unfavorable, or conversely to decrease the second target distance when he judges the grip conditions to be favorable.

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

[0103] The second target distance is then further determined based on the adjustable weighting factor.

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

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

[0106] The ACC system thus receives the second target distance as a setpoint. When the grip conditions are poor and correspond for example to a risk of skidding during braking, having the effect of extending a stopping distance of the first vehicle 10, the DIV is then defined as a function of these unfavorable grip conditions. The DIV is thus increased, the level of safety of the passengers of the first vehicle 10 is then 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 in order to avoid any risk of activation of an anti-skid system following excessively sudden deceleration.

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

[0109] The device 2 is for example configured for the implementation of the operations described with regard to [Fig.l] and / or the steps of the method described with regard to [Fig.3]. Examples of such a device 2 include, but are not limited to, a on-board electronic equipment such as a vehicle's on-board computer, an electronic calculator such as an ECU ("Electronic Control Unit"), a smartphone, a tablet, a laptop. The elements of the device 2, individually or in combination, can be integrated into a single integrated circuit, into several integrated circuits, and / or into discrete components. The device 2 can be produced in the form of electronic circuits or software (or computer) modules or even 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 method and / or for executing the instructions of the software(s) 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 corresponding for example to a volatile and / or non-volatile memory and / or comprises a memory storage device which may comprise volatile and / or non-volatile memory, such as EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, magnetic or optical disk.

[0111] The computer code of the embedded software(s) comprising the instructions to be loaded and executed by the processor is for example stored in the 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 (from the English “Telematic Control Unit” or in French “Telematic Control Unit”), for example via a communication bus or through dedicated input / output ports.

[0113] According to a particular and non-limiting exemplary embodiment, the device 2 comprises 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 a tablet for example. The interface elements of the block 22 comprise one or more of the following interfaces: - RF radio frequency interface, for example Wi-Fi® type (according to IEEE 802.11), for example in the 2.4 or 5 GHz frequency bands, or Bluetooth® type (according to IEEE 802.15.1), in the 2.4 GHz frequency band, or Sigfox type using UBN (Ultra Narrow Band) radio technology, or LoRa in the 868 MHz frequency band, LTE (Long-Term Evolution), LTE-Advanced; - USB interface (from the English “Universal Serial Bus” or “Universal Serial Bus” in French); - HDMI interface (from the English “High Definition Multimedia Interface”).

[0114] According to another particular and non-limiting exemplary embodiment, the device 2 comprises a communication interface 23 which makes it possible to establish communication with other devices (such as other computers of the on-board system or on-board 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.The communication interface 23 corresponds for example to a wired network of the CAN (Controller Area Network), CAN FD (Controller Area Network Flexible Data-Rate), FlexRay (standardized by the ISO 17458 standard), Ethernet (standardized by the ISO / IEC 802-3 standard) or LIN (Local Interconnect Network).

[0115] According to a particular and non-limiting exemplary 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 speakers and / or other peripherals (projection system) via respective output interfaces. According to a variant, one or other of the external devices is integrated into the device 2.

[0116] [Fig. 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 exemplary embodiment of the present invention. The method is for example implemented by a device on board the first vehicle 10 or by the device 2 of [Fig. 2].

[0117] In a first step 31, first data representative of a 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 grip conditions of the first vehicle 10 are received.

[0120] In a fourth step 34, a correction coefficient of 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 a variant, the variants and examples of the operations described in relation to [Fig.l] apply to the steps of the method of [Fig.3].

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

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

Claims

Claims

1. Method for controlling an adaptive speed control system, called 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 representative of 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 representative of grip conditions of said first vehicle (10); - determining (34) a correction coefficient of said first target distance as a function of said second data; - determining (35) a second target distance as a function of said first target distance and said correction coefficient; - controlling (36) said ACC system as a function of said second target distance.

2. Method according to claim 1, for which said second data comprises: - data representative of an activation state of a windscreen wiper system fitted to the first vehicle (10), and - data representative of slippage of at least one wheel of the first vehicle (10).

3. A method according to claim 1 or 2, which further comprises a step of receiving third data representative of an adjustable weighting factor, said second target distance being further determined as a function of said adjustable weighting factor.

4. Method according to one of claims 1 to 3, for which said correction coefficient is between 1 and 1.

5.

5. Method according to one of claims 1 to 4, for which said correction coefficient is equal to 1 when said speed of the first vehicle (10) is less than a threshold value.

6. Method according to one of claims 1 to 5, which further comprises a step of receiving fourth data representative of driving conditions of the first vehicle (10), said corrective coefficient being further determined as a function of said fourth data.

7. Method according to one of claims 1 to 6, for which said 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 (10), - a coefficient representative of a reaction time of an on-board system of the first vehicle (10), - G a coefficient of gravity, and - a coefficient representative of a level of grip of the first vehicle (10) on a road.

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 (2) for controlling an adaptive vehicle speed regulation system, said device (2) comprising a memory (21) associated with at least one processor (20) configured for implementing the steps of the method according to any one of claims 1 to 7.

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

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