Method and device for controlling an adaptive cruise control system of an autonomous vehicle

Abstract

The invention relates to a method and a device for controlling an adaptive cruise control system, called ACC system, of an autonomous vehicle, called ego vehicle, the method comprising the steps of: Receiving (201) first data; Receiving (202) second data; Determining (203) a first speed and a first distance from a detection of the second vehicle; Receiving (204) third data; Determining (205) a trajectory of said ego vehicle; Determining (206) a second speed and a second distance; Selecting (207) said first speed and said first distance, or said second speed and said second distance, as a speed of the target and a distance from the target of said ACC system, said selection being based on said first data, on said second data and on said third data. Figure to be published for the abstract: Figure 2

Description

Title of the invention: Method and device for controlling an adaptive cruise control system of an autonomous vehicle Technical field of the invention

[0001] The invention is in the field of autonomous vehicle driving assistance systems. In particular, the invention relates to a method and a device for controlling an adaptive cruise control system of an autonomous vehicle. State of the art

[0002] The term "vehicle" means any type of vehicle such as a motor vehicle, a moped, a motorcycle, a storage robot in a warehouse, etc. The term "autonomous driving" of an "autonomous vehicle" means any method capable of assisting the driving of the vehicle. The method may thus consist of partially or totally steering the vehicle or providing any type of assistance to a natural person driving the vehicle. The method thus covers all autonomous driving, from level 0 to level 5 in the OICA scale, for International Organization of Motor Vehicle Manufacturers.

[0003] Methods capable of assisting the driving of the vehicle are also called AD AS (from the English acronym "Advanced Driver Assistance Systems"), AD AS functions, AD AS systems or driving assistance systems. Among these AD AS systems, an adaptive cruise control is known.

[0004] Adaptive cruise control is also known as ACC or ACC system (from the English acronym "Auto Cruise Control"). This system automatically maintains a vehicle speed, called ego vehicle, at a value set by an occupant or driver of the ego vehicle, a value called the set speed, while respecting a safety distance from a vehicle, called the target vehicle, preceding the ego vehicle. For example, a target vehicle is a land vehicle, any type of obstacle, any disturbance, etc. The safety distance is determined from an inter-vehicle time, Tiv, set by the driver and from an ego vehicle speed.

[0005] An ACC uses data from several sensors, generally including a camera installed at the top of a windshield of the vehicle and a radar or lidar installed in a front bumper of the vehicle. These sensors are capable of detecting and identifying objects in an environment close to the vehicle. A vehicle equipped with an ACC is capable of detecting several objects in front of the vehicle, and is capable of determining data associated with these objects such as a speed, a position, a distance, an inter-vehicle distance, a shape, characteristics typifying or defining the object, ... An object can be a land vehicle, any type of obstacle, any disturbance ... These sensors are also configured to identify characteristics of a road and lanes on which the vehicle is traveling, or anything else that is recognized by these sensors.

[0006] A selection of a target vehicle controls the adaptive cruise control. This selection makes it possible to determine, on the one hand, a speed of the target vehicle, called the target speed, and, on the other hand, a distance between the target vehicle and the ego vehicle, called the target distance. The target speed and the target distance are important input elements to the ACC system in order to regulate the speed of the ego vehicle while maintaining a safe distance from the target vehicle. There are still situations where the selection of the target vehicle to control the adaptive cruise control is crucial.

[0007] In particular, this is the case when the ego vehicle, first vehicle, is traveling on a traffic lane of a road, called the first lane, with an initial speed, behind a second vehicle, the second vehicle traveling on the first lane with a speed lower than the initial speed, and when the ego vehicle changes lane to go to a second lane, a lane adjacent to the first lane, the second lane being a lane on which the ego vehicle can travel with a speed greater than the initial speed. In this situation, an occupant of the ego vehicle may wish to overtake the target vehicle. Before the start of the overtaking maneuver, the second vehicle is selected, by the ACC system, as the target vehicle and remains so for at least one second when the ego vehicle changes lane.The ACC having a target vehicle and having to respect an inter-vehicle distance will prevent the ego vehicle from accelerating and therefore limit the expected dynamics, an acceleration, of the ego vehicle. Summary of the invention.

[0008] An object of the present invention is to remedy the aforementioned problem, in particular to improve the control of an adaptive cruise control of a vehicle by better selection of a target vehicle, thus making it possible to improve the expected dynamics of the vehicle.

[0009] To this end, a first aspect of the invention relates to a method for controlling an adaptive cruise control system, called an ACC system, of an autonomous vehicle, called an ego vehicle, said ego vehicle traveling on a road comprising at least two traffic lanes, a first lane and a second lane, said ego vehicle traveling on said first lane, said second lane being adjacent to said first lane, a second vehicle traveling on said first lane in front of said first vehicle in a direction of travel of said first vehicle, the method comprising the steps of: • Reception of first data characterizing at least two lanes, in particular said first lane and said second lane, said first data making it possible to geographically model, in relation to said vehicle, a location of said lanes and of demarcation lines of said lanes; • Reception of second data characterizing detected objects, said second data making it possible to determine a speed of each detected object, and making it possible to geographically locate, in relation to said vehicle, a location of each detected object; • Determining a first speed and a first distance from a detection of the second vehicle, said detection being based on said first data and said second data; • Reception of third data representative of a movement of said ego vehicle; • Determination, from said third data, of a trajectory of said ego vehicle, called determined trajectory, said determined trajectory being representative of a trajectory of said ego vehicle over a predetermined time horizon; • Determination of a second speed and a second distance either from a detection of an object, called the third vehicle, said third vehicle being on said determined trajectory, said detection being based on said second data and said determined trajectory, or, in the absence of detection of an object on said determined trajectory, from a predetermined speed and a predetermined distance; • Selecting said first speed and said first distance, or said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data.

[0010] Thus, the second vehicle may no longer be selected as the target vehicle for the ACC system based on the trajectory of the ego vehicle, even if the second vehicle is in front of the ego vehicle, the second vehicle and the ego vehicle traveling on the same first lane. The control of the cruise control system is also more reliable, it is a function of two different determinations, each determination using a different data set.

[0011] Advantageously, said first data comprise data further enabling the type of track to be characterized, said method further comprising steps of: • Determination, from said first data, whether said second lane is an overtaking lane for said first lane; • Detection (208) of activation of a turn signal of the vehicle, said turn signal indicating said second lane, said second lane being an overtaking lane of said first lane; • Selecting (209) said second speed and said second distance as target speed and target distance of said ACC system, if said second lane is an overtaking lane of said first lane.

[0012] As long as the ego vehicle has not changed lanes, that is, as long as the ego vehicle has not completely crossed a boundary line between the first and second lanes, the ego vehicle is traveling on the same lane, the first lane, as the second vehicle. Since the second vehicle is traveling on the same lane as the ego vehicle, current ACC systems then keep the second vehicle as the target vehicle. The second vehicle will therefore limit the dynamics of the ego vehicle. The ego vehicle will not be able to accelerate autonomously to overtake the second vehicle because a current ACC system will keep a safe distance from the second vehicle and therefore limit the speed of the ego vehicle.

[0013] In the present case, upon identification that the ego vehicle wishes to overtake the second vehicle, i.e. that the ego vehicle shows a change of trajectory by taking an overtaking lane, the second target vehicle is no longer selected as a target vehicle of said ACC system. Only a vehicle on the trajectory of the ego vehicle will be selected as a target vehicle for the ACC system. Only a vehicle on the trajectory of the ego vehicle will limit a dynamic of the ego vehicle. At the start of the maneuver, just after triggering the indicator, if the ego vehicle has not clearly changed direction (detected for example by a steering angle, lateral acceleration, yaw rate or other data, taken alone or in combination, greater than a predetermined threshold), the second vehicle will be on the trajectory of the ego vehicle.In this case, the second vehicle is the third detected vehicle, and the second vehicle can be taken as the target vehicle for the ACC system. In other words, as long as the second vehicle is on the trajectory of the ego vehicle, the second vehicle is taken as the third vehicle and is taken as the target vehicle. As soon as the second vehicle is no longer on the trajectory of the ego vehicle, it will no longer be selected as the third vehicle and as the target vehicle. Thus, on a highway for example, the second vehicle is no longer selected as the target vehicle earlier, several seconds, compared to current ACC systems. With the present invention, compared to existing ACC systems, the ego vehicle accelerates more and earlier, in a safe manner because . the second vehicle on the first lane is taken into account by the ACC system only as long as the second vehicle is on the path of the ego vehicle.

[0014] Advantageously, said method further comprises steps of: • Detection of deactivation of said indicator or of a stop of indication, by the indicator, of said second channel; • Selecting said first speed and said first distance, or said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data.

[0015] Advantageously, said method further comprises the steps of: • Activation of a timer following said detection of activation of said indicator; • Detection that the timer indicates a time greater than a predetermined time, said predetermined time being strictly positive; • Selecting said first speed and said first distance, or said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data.

[0016] Advantageously, the first data also characterize a third lane, said third lane being adjacent to said first lane, said third lane being a lane other than said second lane, said third lane being determined as not being an overtaking lane of said first lane, said method further comprises steps of: • Determination, from said first data and said third data, that said ego vehicle is heading towards said third path; • Selecting said first speed and said first distance, or said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data.

[0017] These steps make it possible to detect an intention not to, or no longer to, overtake the second vehicle, the ego vehicle will certainly remain in the first lane. Thus, if during the overtaking maneuver, it is detected that the overtaking maneuver is either modified or interrupted by an occupant of the ego vehicle, or has taken too long, the second vehicle, traveling on the same first lane, can be selected. The control of the cruise control system is also more reliable, it is a function of two different determinations, each determination using a different data set.

[0018] Advantageously, the method further comprises the steps of: • Determination, from said first data and said third data, of a change of traffic lane of the vehicle; • Resetting of said process.

[0019] Advantageously, following the resetting of the method, the timer is also reset to 0, and if the indicator has remained activated, the indicator is detected activated.

[0020] Thus, the method is reset to manage the case of several consecutive lane changes.

[0021] A second aspect of the invention relates to a device comprising a memory associated with at least one processor configured to implement the method according to the first aspect of the invention.

[0022] The invention also relates to a vehicle comprising the device.

[0023] The invention also relates to a computer program comprising instructions which, when the program is executed by the device according to the second aspect of the invention, lead the latter to implement the method according to the first aspect of the invention. Brief description of the figures

[0024] Other characteristics and advantages of the invention will emerge from the description of the non-limiting embodiments of the invention below, with reference to the appended figures, in which:

[0025] [Fig-1] schematically illustrates a device, according to a particular example of embodiment of the present invention.

[0026] [Fig.2] schematically illustrates a method of controlling a regulation system adaptive speed of an autonomous vehicle, according to a particular exemplary embodiment of the present invention. Detailed description of the invention

[0027] The invention is described below in its non-limiting application to the case of an autonomous motor vehicle, called an ego vehicle, traveling on a road or on a traffic lane. Other applications such as a robot in a storage warehouse or a motorcycle on a country road are also conceivable.

[0028] [Fig.l] represents an example of a device 101 included in the vehicle, in a network (“cloud”) or in a server. This device 101 can be used as a centralized device in charge of at least certain steps of the method described below in reference to [Fig.2]. In one embodiment, it corresponds to an autonomous driving computer.

[0029] In the present invention, the device 101 is included in the vehicle.

[0030] This device 101 can take the form of a box comprising circuits printed, from any type of computer or even from a mobile phone (“smartphone”).

[0031] The device 101 comprises a random access memory 102 for storing instructions for the implementation by a processor 103 of at least one step of the method as described above. The device also comprises a mass memory 104 for storing data intended to be retained after the implementation of the method.

[0032] The device 101 may further comprise a digital signal processor (DSP) 105. This DSP 105 receives data to format, demodulate and amplify, in a manner known per se, this data.

[0033] The device 101 also comprises an input interface 106 for receiving the data implemented by the method according to the invention and an output interface 107 for transmitting the data implemented by the method according to the invention.

[0034] For example, the input interface 106 can receive the following data: position or geographical location of the vehicle, speed and / or acceleration of the vehicle, set or predetermined positions / speeds / accelerations, engine speed, position and / or travel of the clutch, brake and / or acceleration pedal, detection of other vehicles or objects, position or geographical location of the other vehicles or objects detected, speed and / or acceleration of the other vehicles or objects detected, states of an input of a human-machine interface (HMI) or of a command of an interface, operating states of sensors, confidence index of data from or processed by sensors and / or devices similar to the device 101. For example, the sensors capable of providing data are: GPS associated or not with mapping, tachometers, accelerometers, RADAR, LIDAR, lasers, ultrasound, camera, etc.

[0035] In the present invention, the input interface 106 can receive first data characterizing at least two lanes, said first data making it possible to geographically model, with respect to said ego vehicle, a location of said lanes and boundary lines of said lanes. The characterization of the lanes received makes it possible to determine whether a lane is an overtaking lane with respect to another lane. The input interface 106 can also receive second data characterizing detected objects, said second data making it possible to geographically locate, with respect to the ego vehicle, a location of said detected objects, and making it possible to determine a relative speed for each detected object, with respect to the speed of the ego vehicle, of said detected objects.The input interface 106 can also receive third data representative of a movement of said vehicle, such as for example a position, speed or longitudinal acceleration. of the vehicle, a position, speed or transverse acceleration of the vehicle, an angle, a speed, an acceleration or a force or torque of a rotation of a steering wheel of the vehicle, a rack, or a device linked to the transverse direction of the vehicle, an angle, a speed an acceleration of a yaw angle of the vehicle, ... The input interface 106 can also receive indicators, probabilities, confidence indices of detection of an object, a vehicle, a lane line, marking lines, ... The input interface 106 can also receive a state of an input of a human machine interface (HMI) or a command of an interface such as an activation of a turn signal, a left or right side relative to the direction of travel of the vehicle, ...

[0036] For example, the output interface 107 can transmit data similar to the data received by the input interface 106 or data such as a vehicle to be selected for an ACC system, a speed of a target vehicle, a distance from a target vehicle, a reset of a process, a timer or detection of activation of a turn signal, an incrementation of a timer, ...

[0037] [Fig.2] schematically illustrates a method for controlling an adaptive cruise control system of an autonomous vehicle, according to a particular embodiment of the present invention. Said adaptive cruise control system is called an ACC system. Said autonomous vehicle is also called an ego vehicle. Said ego vehicle travels on a road comprising at least two traffic lanes, a first lane and a second lane. Said ego vehicle travels on said first lane. Said second lane is adjacent to said first lane, the second lane is therefore immediately adjacent to the first lane. The second lane is thus a lane adjoining the first lane, a vehicle traveling on the first lane can, during a lane change, travel on the second lane by crossing a boundary line between the first lane and the second lane.The second lane may be to the left or to the right of the first lane, left and right being defined relative to a normal direction of travel of a vehicle normally traveling on the lane. A second vehicle travels on said first lane in front of said first vehicle in a direction of travel of said first vehicle. The method comprises several steps.

[0038] Step 201, Rxl, is a step of receiving first data characterizing at least two lanes, in particular said first lane and said second lane, said first data making it possible to geographically model, with respect to said vehicle ego, a location of said lanes and of demarcation lines of said lanes.

[0039] The first data are for example received by the input interface 106. The first data can be sent by information providers such as by a vehicle sensor and / or by a device similar to the device 101. For example, the first data may be provided by processing captured images, by mapping, ..., or a device similar to the device 101 which combines the information from these data providers.

[0040] The first data characterizes detected lanes, including at least two lanes, the first lane and the second lane. This characterization makes it possible to determine and / or receive a number of lanes of a road, a width of a lane, a length of the lanes, ground markings, a type of marking (continuous line, guide line, deterrent line, edge lines, etc.), a positioning of the lanes relative to the vehicle.

[0041] Step 202, Rx2, is a step of receiving second data characterizing detected objects, said second data making it possible to determine a speed of each detected object, and making it possible to geographically locate, relative to said vehicle ego, a location of each detected object.

[0042] The second data are for example received by the input interface 106. The second data can be emitted from the information providers such as by a sensor of the vehicle and / or by a device similar to the device 101. For example, the second data can be provided by processing captured images, by sensors such as a radar, a lidar, ..., or a device similar to the device 101 which combines the information from these information providers.

[0043] The second data characterizes the detected objects. An object can be a land vehicle, any type of obstacle, any disturbance, etc. For example, each object is associated with a speed, a position, an inter-vehicle distance, a shape, characteristics typifying or defining the object, etc.

[0044] Step 203, V1D1, is a step of determining a first speed and a first distance from a detection of the second vehicle, said detection being based on said first data and said second data.

[0045] From the first data, a model of the lanes of the road on which the ego vehicle is traveling is determined. Different types of models are possible. This modeling can be a geographical representation of the lanes, a mathematical modeling of the geometry of the lanes, etc. These models can be expressed in different reference frames. For convenience, it is simpler to link these models with respect to a reference frame of the ego vehicle, the origin of the reference frame being able to be the middle of the front axle, the center of gravity, the front left side of the vehicle, or other.

[0046] From the second data, it is possible to determine the location of the detected objects relative to a reference point, for convenience relative to a reference point of the vehicle. It is then possible to determine whether one of the detected objects is circulating on said first lane, the lane on which said ego vehicle is traveling. This step makes it possible to detect whether an object, or vehicle, is traveling on the same lane as the lane on which the ego vehicle is traveling. The second vehicle traveling on said first lane is therefore detected. The second data makes it possible to determine a speed of the second vehicle and a distance from the second vehicle. The speed of the second vehicle and the distance from the second vehicle may be relative to the ego vehicle.

[0047] Step 204, Rx3, is a step of receiving third data representative of a movement of said vehicle. The third data are for example received by the input interface 106. The third data can be emitted from information providers such as by a sensor of the vehicle and / or by a device similar to the device 101. For example, the third data can be provided by processing captured images, by sensors such as a radar, a lidar, accelerometers, odometers, tachometers, inertial units, etc., or a device similar to the device 101 which combines the information from these providers.For example, the data may also be a steering wheel rotation angle, a rack position, a yaw rate (speed of rotation about a vertical axis relative to a horizontal plane of the vehicle passing through a reference point of the vehicle or relative to a horizontal plane of the road of a projection of a reference point of the vehicle on the road), a position of the vehicle... The data may be logged, a history of the data over a time horizon, for example one second, ten seconds or any other value, is provided or is saved in the memory 102.

[0048] Step 205, Traj, is a step of determining, from said third data, a trajectory of said ego vehicle, called determined trajectory, said determined trajectory being representative of a trajectory of said ego vehicle over a predetermined time horizon. For example, the predetermined time horizon is 1 second, 10 seconds or any other values. These other values ​​may depend on other data such as the speed of the vehicle. The trajectory predicts the possible positions and locations of the ego vehicle over a time horizon, relative to the ego vehicle and relative to the lanes.

[0049] Said third data makes it possible to model a trajectory of said ego vehicle. This modeling can be carried out in several ways: geographical representation, mathematical temporal modeling of the future trajectory, extrapolation from historical data, etc. The future trajectory of the ego vehicle is determined in relation to the current location, at the time of determination, of the ego vehicle.

[0050] Step 206, V2D2 is a step of determining a second speed and a second distance either from a detection of an object, called third vehicle, said third vehicle being on said determined trajectory, said detection being based on said second data and said determined trajectory, or, in the absence of detection of an object on said determined trajectory, from a predetermined speed and a predetermined distance.

[0051] The second data makes it possible to locate, and, for example, to place in a cartographic representation, the detected objects relative to the ego vehicle. The trajectory determined in step 205 makes it possible to predict the future trajectory of the ego vehicle relative to the current location of the ego vehicle. It is then possible to detect whether a detected object is on the predicted trajectory of the ego vehicle. In one operating mode, a trajectory for each detected object is also detected. Methods for determining the trajectory of a detected object are known. It is then possible to determine whether the future trajectory of the ego vehicle intercepts a future trajectory of a detected object.

[0052] If an object is detected on the predicted trajectory of the ego vehicle, this object is said to be a third vehicle. The second data makes it possible to determine a speed of the third vehicle and a distance from the third vehicle. The speed of the third vehicle and the distance from the third vehicle may be relative to the ego vehicle. In the event of detection of an object, the second speed is the speed of the third vehicle, and the second distance is the distance from the third vehicle.

[0053] In the absence of detection of an object on the predicted trajectory of the ego vehicle, the second speed is a predetermined speed, and the second distance is a predetermined distance. For example, the predetermined speed may be a set speed set by an occupant of the ego vehicle, and the predetermined distance may be a set distance set by an occupant of the ego vehicle. The set distance set by an occupant of the ego vehicle, or inter-vehicle distance, may be determined by a set time, called inter-vehicle time, set by the occupant of the ego vehicle, according to a relationship: inter-vehicle distance is equal to the inter-vehicle time multiplied by a speed of the ego vehicle.

[0054] Advantageously, if the occupant of the ego vehicle does not set a target distance or does not set a target time, the target distance and the target time may have default values, or may be determined by the first data, the second data or other data. For example, a traffic speed limit is determined by a characteristic of the lane on which the ego vehicle is traveling or by a characteristic of the destination lane of the ego vehicle (second lane for example). The characteristic of a lane may be determined by traffic sign recognition, by geolocation associated with mapping and a database, etc.

[0055] Step 207, Selectl2, is a step of selecting said first speed and said first distance, or, said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data.

[0056] Thus, the second vehicle may no longer be selected as the target vehicle for the ACC system based on the trajectory of the ego vehicle, even if the second vehicle is in front of the ego vehicle, the second vehicle and the ego vehicle traveling on the same first lane. The control of the cruise control system is also more reliable, it is a function of two different determinations, each determination using a different data set.

[0057] The selection between the first speed and distance and the second speeds and distance can be carried out in several ways. For example, this selection is made from the detected vehicle (second vehicle or third vehicle) closest to the ego vehicle, from the detected vehicle traveling the slowest, from probability or confidence indicators on each of the first, second and third data, ... For example, a low probability indicator will be attributed to the determination of the first speed and distance if the first data are unreliable (road markings / lane boundary lines poorly identified due to weather conditions, vehicles traveling on said lines, ...). The probability indicator can become even lower depending on a history of the probability indicator.

[0058] Step 208, TestC, is a step of detecting an activation of a turn signal of the vehicle, said turn signal indicating said second lane, said second lane being an overtaking lane of said first lane.

[0059] First of all, from said first data and the characterization of the lanes, it is possible to determine whether said second lane is an overtaking lane of said first lane. An overtaking lane of the first lane is a lane adjacent to the first lane on which the vehicle can travel faster than the speed of the second vehicle in order to be able to overtake the second vehicle. In one operating mode, the maximum speed of travel on the second lane is determined by recognition of the type of the second lane, recognition of a regulatory speed limit (motorway, traffic sign, etc.).

[0060] The detection of the activation of the turn signal of the ego vehicle can be determined by information processing, the information being received by the input interface 106. It is known that the turn signal is used to signal a change of direction or change of lane. The turn signal indicates the direction in which the vehicle is heading, it is either a left side or a right side, the left and right sides being defined in relation to the normal direction of travel of the vehicle. The input interface can receive a signal representative of an activated indicator (for example a position of a stalk, a control that can be found under a steering wheel) and receive a signal representative of one side of the vehicle, left side or right side. For example, the signal transmitter is a device similar to device 101, a device linked to the stalk.

[0061] In this case, it is tested whether the side indicated by the turn signal is an overtaking lane of the first lane. If so, the method has detected an intention to overtake the second vehicle. The method then proceeds to step 209.

[0062] Advantageously, this step comprises a sub-step of activating a timer following said detection of activation of said indicator. The timer is used to measure the duration from the moment when the intention to overtake the second vehicle was detected. This duration can be used in a future step such as in step 211 described below.

[0063] Step 209, Select2, is a step of selecting said second speed and said second distance as the target speed and target distance of said ACC system, if said second lane is an overtaking lane of said first lane. Having detected an intention to overtake the second vehicle traveling on the first lane, the selection of a target vehicle, therefore of a target speed and a target distance, traveling on the same first lane is no longer taken into account. Only a vehicle, if detected, on the future trajectory of the ego vehicle is taken into account by the ACC system. The ego vehicle accelerates significantly earlier, approximately 1 second (other values ​​are possible ranging from a few tens of milliseconds to several seconds, the duration depending on the speed of the ego vehicle, the distance from the second vehicle, configuration parameters of the ACC system, etc.)) than the current ACC system while ensuring a safe distance (as long as the second vehicle is on the path of the ego vehicle, the second vehicle is taken into account by the ACC system).

[0064] The ego vehicle changing direction, therefore trajectory, other vehicles, not traveling on the first lane, may require adapting the speed regulation by the ACC system. If a third vehicle is detected on the trajectory of the ego vehicle, this third vehicle becomes the target vehicle. In the absence of a vehicle detected on the trajectory of the ego vehicle, the second speed is a predetermined speed and the second distance is a predetermined distance.

[0065] In certain situations, it is necessary to deactivate a selection of the target speed and the target distance by only a detection or absence of detection of a vehicle on the trajectory of the ego vehicle. Steps 210, 211 and 212 give stopping conditions, to return to a selection of said first speed and said first distance, or, of said second speed and said second distance, such as a target speed and a target distance from said ACC system, said selection being based on said first data, said second data and said third data, as in step 207.

[0066] Step 210, TestA, is a step of detecting a deactivation of said indicator or a stop of indication, by the indicator, of said second lane. Thus, a lane change stop is determined.

[0067] Step 211, TestM, is a step of detecting that the timer indicates a time greater than a predetermined time, said predetermined time being strictly positive, the timer being initialized in step 208 upon detection of an intention to change lane to overtake the second vehicle. The timer is used to measure the duration from the moment when the intention to overtake the second vehicle was detected. If this duration becomes too great then there is certainly a situation that does not allow the second vehicle to be overtaken safely. For example, the situation is another vehicle traveling on the second lane at the level of the ego vehicle. For example, the predetermined duration is preferably between 5 and 10 seconds, other values ​​are possible and may depend on the driving environment (other vehicles, traffic density, speed of the ego vehicle, etc.).

[0068] Step 212, TestV, is a step in which the first data also characterizes a third lane, said third lane being adjacent to said first lane, said third lane being a lane other than said second lane, said third lane being determined as not being an overtaking lane of said first lane. Said method further comprises a step of determining, from said first data and said third data, that said ego vehicle is heading towards said third lane. In this situation, the indication of the side detected in step 208 is erroneous, for example, the driver has chosen the wrong side, the ego vehicle ultimately heads towards another lane, a slower lane.For example, the ego vehicle, traveling on a highway, initially intended to overtake the second vehicle in the second lane, a left-hand lane, but, before overtaking the second vehicle, the ego vehicle changes its intention and wishes to take the right-hand lane which is a highway exit.

[0069] If the conditions in steps 210, 211 or 212 are verified, the method proceeds to step 213, a step similar to step 207 described previously.

[0070] Step 214, TestF, is a step of determining, from said first data and said third data, a change of traffic lane of the vehicle.

[0071] The lane change determination can be carried out in different ways. For example, from the first data, the second data, it is possible to determine the moment when a right rear wheel of the vehicle, for a left lane change, crossed a boundary line between the first lane and the second lane. This determination can also be made by analyzing measurements of lateral acceleration, steering angle, yaw rate and / or other measurements related to the movement of the ego vehicle.

[0072] Step 214 tests the end of the lane change, and if so the method is reset (step 215). Advantageously, following the reset of the method, the timer is also reset to 0, and if the indicator has remained activated, the indicator is detected, again, activated. Thus, the method manages the case of several consecutive lane changes.

[0073] The present invention is not limited to the embodiments described above as examples: it extends to other variants.

[0074] Thus, an exemplary embodiment has been described above in which the steps described with reference to [Fig. 2] have been carried out in a specific order. A different order is also conceivable. For example, step 203 can be carried out after step 205, steps 201, 202, 203 can be reversed or carried out simultaneously, as can steps 210, 211, 212 and 214.

Claims

Claims

1. Method for controlling an adaptive cruise control system, called ACC system, of an autonomous vehicle, called ego vehicle, said ego vehicle traveling on a road comprising at least two traffic lanes, a first lane and a second lane, said ego vehicle traveling on said first lane, said second lane being adjacent to said first lane, a second vehicle traveling on said first lane in front of said first vehicle in a direction of travel of said first vehicle, the method comprising the steps of: Reception (201) of first data characterizing at least two lanes, in particular said first lane and said second lane, said first data making it possible to geographically model, in relation to said vehicle, a location of said lanes and of demarcation lines of said lanes; Reception (202) of second data characterizing detected objects, said second data making it possible to determine a speed of each detected object, and making it possible to geographically locate, relative to said vehicle, a location of each detected object; Determining (203) a first speed and a first distance from a detection of the second vehicle, said detection being based on said first data and said second data; Reception (204) of third data representative of a movement of said vehicle ego; Determination (205), from said third data, of a trajectory of said ego vehicle, called determined trajectory, said determined trajectory being representative of a trajectory of said ego vehicle over a predetermined time horizon; Determination (206) of a second speed and a second distance either from a detection of an object, called a third vehicle, said third vehicle being on said determined trajectory, said detection being based on said second data and said determined trajectory, or, in the absence of detection of an object on said determined trajectory, from a predetermined speed and a predetermined distance; Selecting (207) said first speed and said first distance, or said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data,

2. on said second data and on said third data; • Determination, from said first data, whether said second lane is an overtaking lane for said first lane; • Detection (208) of activation of a turn signal of the vehicle, said turn signal indicating said second lane, said second lane being an overtaking lane of said first lane; • Selecting (209) said second speed and said second distance as target speed and target distance of said ACC system, if said second lane is an overtaking lane of said first lane; • Activation of a timer following said detection of activation of said indicator; • Detection (211) that the timer indicates a time greater than a predetermined time, said predetermined time being strictly positive; • Selecting (213) said first speed and said first distance, or said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data. The method of claim 1, wherein said method further comprises the steps of: • Detection (210) of deactivation of said indicator or of a stop of indication, by the indicator, of said second channel; • Selecting (213) said first speed and said first distance, or said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data.

3. A method according to claims 1 or 2, wherein the first data also characterizes a third lane, said third lane being adjacent to said first lane, said third lane being a lane other than said second lane, said third lane being determined not to be an overtaking lane of said first lane, said method further comprises steps of: • Determining (213), from said first data and said third data, that said ego vehicle is heading towards said third lane; • Selecting (211) said first speed and said first distance, or, said second speed and said second distance, as a target speed and a target distance of said ACC system, said selection being based on said first data, on said second data and on said third data.

4. Method according to claims 1 to 3, in which the method further comprises the steps of: • Determining (214), from said first data and said third data, a change of traffic lane of the ego vehicle; • Resetting (215) said method.

5. The method of claim 4, wherein, following the resetting of the method, the timer is also reset to 0, and if the turn signal has remained activated, the turn signal is detected activated.

6. Device (101) comprising a memory (102) associated with at least one processor (103) configured to implement the method according to one of the preceding claims.

7.

8. Vehicle comprising the device according to the preceding claim. Computer program comprising instructions which, when the program is executed by the device (101), cause the latter to implement the method according to one of claims 1 to 5.

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