Method and apparatus for controlling the trajectory of a vehicle traveling along a lane and associated vehicles - Patents.com

Abstract

The present invention relates to a method for controlling in real time the path of a motor vehicle traveling in a lane, the method comprising the steps of detecting a corner in the lane and then, when the motor vehicle enters said corner, determining a first amount and a second amount of a plurality of successive sampling increments based on state variables characterizing movement of the motor vehicle; determining a first stored value and a second stored value, the first stored value depending on a first amount determined at a current sampling increment and a first amount determined for at least one of the preceding sampling increments, and the second stored value depending on a second amount determined at a current sampling increment and a second amount determined for at least one of the preceding sampling increments; The method includes the steps of storing the first and second stored values ​​determined for each sampling increment in a memory, then determining an understeer gradient value according to the first and second stored values ​​stored in the memory when the motor vehicle exits the corner, and determining a command for the motor vehicle based on the understeer gradient value thus determined.

Description

[Technical field]

[0001] The present invention relates generally to controlling the path of a motor vehicle, particularly to keeping the vehicle in its lane during turns.

[0002] The invention more particularly relates to a method and a device for controlling the path of a motor vehicle traveling in a lane.

[0003] The invention equally relates to a motor vehicle including a route control device of this kind. [Background technology]

[0004] Autonomous and semi-autonomous automated vehicles are designed to travel on public roads without intervention by a driver. To this end, the automated vehicle is equipped with a series of digital sensors that allow the collection of data characterizing the status of the automated vehicle and the environment. The automated vehicle is also provided with software that allows the analysis of that data. The software uses algorithms to then generate commands to steer the automated vehicle. In particular, the software is designed to generate a control law that controls the assisted steering system in such a manner as to keep the automated vehicle centered in the lane. This type of control law is conventionally called a Lane Centering Assist (LCA) law.

[0005] The control method makes it possible, inter alia, to adjust the turning angle of the steerable wheels of the motor vehicle. This turning angle depends on the curvature of the lane, on the speed of the motor vehicle and on a parameter known as the understeer gradient, which quantifies the behavior of the motor vehicle when it turns. The understeer gradient is defined as a gradient of 1 m / s 2 may be defined as the angle that should be imparted to a wheel for a motor vehicle subjected to a lateral acceleration of

[0006] This parameter is not measurable. Moreover, the range of variation of this parameter is quite large, which can lead to poor set points for the turning angle and thus to significant off-centering of the motor vehicle when turning.

[0007] Patent application FR3104106 describes a method for determining the understeer gradient, which is based on modifying the amount of oversteer relative to a nominal value as soon as it is observed.

[0008] However, changes encountered on the path of the motor vehicle, e.g. changes in the load of the motor vehicle, which have a significant effect on the value of the understeer gradient (and therefore on the value of the turning angle), are not taken into account instantaneously when the motor vehicle is moving. Summary of the Invention

[0009] The invention proposes to improve the control of the path of a motor vehicle when turning by taking into account in real time the turns encountered during the movement of the motor vehicle.

[0010] According to the invention, more particularly, there is provided a method for controlling the path of a motor vehicle traveling in a lane, comprising the steps of: detecting a turn in a lane; and then, when the motor vehicle is entering the turn, determining a first amount and a second amount of a plurality of successive sampling increments based on state variables characterizing movement of the motor vehicle; determining a first stored value and a second stored value, the first stored value being a function of a first amount determined for the current sampling increment and a first amount determined for at least one of the preceding sampling increments, and the second stored value being a function of a second amount determined for the current sampling increment and a second amount determined for at least one of the preceding sampling increments; storing in a memory the first and second stored values ​​determined for each sampling increment; and then, when the motor vehicle exits the turn, determining an understeer gradient value as a function of the first stored value and a second stored value stored in a memory; determining a command for the motor vehicle based on the determined understeer gradient value; A method is proposed, which includes:

[0011] Therefore, thanks to the present invention, the understeer gradient value is determined in real time at regular intervals while the motor vehicle is moving. The understeer gradient value is determined and updated, more particularly, for each turn throughout the movement of the motor vehicle in the lane. The motor vehicle path control set point is therefore advantageously adjusted in real time as well. This then allows the motor vehicle to be as close as possible to the ideal path in the center of the lane (in straight lines as well as in turns) without leading to a sudden change of path. This therefore allows the comfort of the motor vehicle passengers to be guaranteed by preventing jolts during path control changes.

[0012] The invention is particularly advantageously applicable in the case of heavy load vehicles or utility vehicles whose load distribution may vary during travel (e.g. during delivery). The understeer gradient is therefore adjusted throughout the travel of the motor vehicle, taking these load changes into account, without external intervention.

[0013] Other advantageous, non-limiting features of the control method according to the invention, taken separately or in all technically possible combinations, are: The first stored value is a function of the sum of a first amount determined for the current sampling increment and a first amount determined for at least one of the preceding sampling increments, and the second stored value is a function of the sum of a second amount determined for the current sampling increment and a second amount determined for at least one of the preceding sampling increments. The state variables characterizing the movement of the motor vehicle are functions of the components of the rotation angle of the wheels of the motor vehicle, the curvature of the lane, the moving speed of the motor vehicle, or the wheelbase of the motor vehicle. Also, prior to the step of detecting a turn, there is the step of initializing an understeer gradient value based on a predetermined value. The step of determining an understeer gradient value is performed for each turn the vehicle makes. There is also a step of correcting the value of the understeer gradient to determine an intermediate value of the understeer gradient, the intermediate value of the understeer gradient being determined based on a weighting between the determined understeer gradient value and a predetermined value. An understeer gradient value is determined based on a ratio between the first stored value and the second stored value. Also, a) determining a first acceleration value and a further second acceleration value of the motor vehicle; b) determining a difference between the first acceleration value and a different second acceleration value; c) if the determined difference is greater than a predefined threshold, further correcting the value of the understeer gradient based on a correction value which is a function of said determined difference. The detection of the turn depends on parameters characterizing the movement of the motor vehicle, at least some of the parameters being selected from the angle of the front wheels of the motor vehicle, the yaw rate of the motor vehicle, the lateral offset between the center of gravity of the motor vehicle and the ideal path, the lateral acceleration of the motor vehicle, or the movement speed of the motor vehicle. The first amount and the second amount are determined using a recursive least squares method as a function of state variables characterizing the movement of the motor vehicle. The step of determining commands for the motor vehicle includes the substep of determining components of rotation angles of wheels of the motor vehicle.

[0014] The invention also relates to a motor vehicle comprising a powertrain, a steering system and the above-introduced device for real-time path control adapted to control the steering system.

[0015] The invention also relates to a device for controlling the path of a motor vehicle traveling in a lane, comprising a computer and a memory provided with a database having a finite number of locations, said computer comprising: Detecting a turn in a lane and then, when the motor vehicle is entering the turn, determining a first amount and a second amount of a plurality of successive sampling increments based on state variables characterizing movement of the motor vehicle; determining a first stored value and a second stored value, the first stored value being a function of a first amount determined for a current sampling increment and a first amount determined for at least one of the preceding sampling increments, and the second stored value being a function of a second amount determined for the current sampling increment and a second amount determined for at least one of the preceding sampling increments; storing in a memory the first and second stored values ​​determined for each sampling increment; and then, when the motor vehicle exits the turn, determining an understeer gradient value as a function of the first stored value and a second stored value stored in a memory; determining a command for the motor vehicle based on the determined understeer gradient value; and This relates to a device designed to

[0016] The invention also relates to a motor vehicle comprising a powertrain, a steering system and the previously introduced device for real-time path control adapted to control the steering system.

[0017] Of course, the various features, variations and embodiments of the invention can be associated with each other in various combinations, provided that they are not incompatible or mutually exclusive.

[0018] The following description, with reference to the attached drawings, given as non-limiting examples, will explain clearly what the invention consists of and how it can be put into practice. [Brief description of the drawings]

[0019] [Figure 1] FIG. 1 shows a schematic diagram of a portion of a motor vehicle. [Diagram 2] This is a representation of the "bicycle" model applied to a motor vehicle traveling in a lane. [Diagram 3] 2 illustrates, in flow chart form, an example of a method according to the present invention for controlling the path of a motor vehicle; [Figure 4] FIG. 1 shows a functional schematic diagram of a closed-loop method for controlling the path of a motor vehicle. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] 1 shows a motor vehicle 1, also referred to below as "vehicle 1", which conventionally has four wheels 3 and a chassis supporting in particular a drive train (i.e. an engine and means for transmitting the engine torque to the drive wheels), a steering system (for example provided with a steering column), bodywork elements and passenger compartment elements.

[0021] 1, the vehicle 1 also includes a control unit 5. The control unit 5 provides commands and control of the various components of the vehicle 1. For example, the control unit 5 can receive information from various digital sensors present in the vehicle 1, such as a speed sensor or a sensor measuring the rotation angle of the front wheels of the vehicle 1.

[0022] The control unit 5 may equally control actuators coupled to a steering column of the vehicle 1, for example by communicating control set points to the actuators. The control unit 5 includes for this purpose a path control device 10. The path control device 10 is adapted to generate control set points. For example, in the case of an autonomous or semi-autonomous vehicle, the path control device 10 enables path control set points to be generated for orienting the vehicle 1 or for keeping the vehicle 1 in a lane, in particular during turns in said lane.

[0023] Here, the control device 10 includes a computer 12 and a memory 14. The memory 14 includes a database. The computer 12 stores in its memory an application consisting of a computer program containing instructions which, when executed by the processor, enable the computer 12 to carry out the methods described below.

[0024] Here, the path of the vehicle 1 is modeled by the so-called "bicycle" model. Figure 2 is a representation of the "bicycle" model applied to a vehicle 1 traveling in a lane. In the context of this model, the vehicle 1 is modeled by a frame and two wheels (as for a bicycle): a steerable front wheel 3a and a non-steerable rear wheel 3b.

[0025] The formula introduced below is a determinant.

[0026] The variables considered in this model are: the yaw velocity of vehicle 1, denoted dψ / dt, corresponding to the rotational velocity of vehicle 1 about a vertical axis passing through the center of gravity G of vehicle 1; the azimuth angle, denoted ψ, corresponding to the angle between the longitudinal axis of the vehicle 1 and the tangent to the path; Ideal Route I d linked to the distance of vehicle 1's center of gravity G from The lateral speed of vehicle 1, shown in TIFF2024526782000002.tif7170, Center of gravity G of vehicle 1 and ideal path I d A lateral offset, denoted by y, which corresponds to the offset between the rotational speed, denoted dδ / dt, of the front wheel 3a relative to the vertical axis, the angle, indicated by δ, of the front wheels 3a, i.e. the angle between the front wheels 3a and the longitudinal axis of the vehicle 1, and Ideal path I on which vehicle 1 should be d The position error integral corresponds to the time integral of the offset of the center of gravity G of the vehicle 1 relative to the target position, and this error integral is expressed by the following equation. ∫-ydt

[0027] The vehicle 1 is therefore represented by what is commonly referred to as a state vector (hereinafter "state data X") defined by the following equation: TIFF2024526782000003.tif43170

[0028] According to the "bicycle" model, the path equation for vehicle 1 is given by: TIFF2024526782000004.tif9170 formula, δ req (unit: radian, hereafter referred to as rad) is the ideal path I d Remain on the ideal path I d is the angle set point (and therefore the control set point) of the front wheels 3a to approximate ρ(unit m -1 ) is the lane curvature (or path curvature in the "bicycle" model), B ρ represents the obstruction data (specifically linked to lane curvature), A represents the dynamic relationship with state data X.

[0029] where matrix A is the respective coefficients c of the cornering stiffness (expressed in Newtons / rad) of the front and rear wheels of vehicle 1. f and c r and the distance I between the center of gravity G of the vehicle 1 and the front drive train, and between the center of gravity G of the vehicle 1 and the rear drive train 1, respectively. f and I r (these distances are represented in FIG. 2), and depend on the mass m of the vehicle 1 (in kg) and on the speed v of the vehicle 1 in the longitudinal direction (in m / s) (hereinafter also called the travel speed of the vehicle 1).

[0030] Wheel cornering stiffness coefficient c f and c r is a concept well known to those skilled in the art. For example, the coefficient of cornering stiffness of the front wheels, c f This gives us the formula F f =2.c f. α f where F f is the lateral sliding force on the front wheels, and α f is the rotation angle of the front wheels.

[0031] In the context of the "Bicycle" model, the measurement Y1 is also expressed as a function of the state data X by the relationship Y1=CX, where C is data including measurements from various digital sensors contained in the vehicle 1.

[0032] In the remainder of the present invention, the lateral acceleration of vehicle 1, which corresponds to the normal component of the acceleration of vehicle 1 in the reference frame coupled to vehicle 1 (and thus perpendicular to the path); and Transverse acceleration of the vehicle 1, which corresponds to the acceleration acting on the vehicle 1 in a manner perpendicular to the direction of movement of the vehicle 1 relative to a reference system linked to the ground. is also defined.

[0033] This "bicycle" model is then used in a control law for the path of the vehicle 1 that is stored in the control unit 5. For example, this control law makes it possible to keep the vehicle 1 in the center of a lane in which it is traveling in a straight line or in part of a turn.

[0034] FIG. 4 shows a closed-loop functional schematic of this control method.

[0035] In Figure 4, X ref corresponds to the ideal path of vehicle 1 in its lane. In practice, this is often a path that passes through the center of the lane in which vehicle 1 is traveling. This ideal path is the path that control unit 5 requests vehicle 1 to achieve (or maintain).

[0036] For this purpose, the control method takes the form of a looped process. According to figure 4, the state of the vehicle 1, in particular the path of the vehicle 1, is given by an element 22. This element 22 is in fact connected to a control unit 5, which determines the rotation angle set point δ for the front wheels. req The controller 10 controls the path of the vehicle 1 in a manner that satisfies the equations (for the state data X and the measurement data Y1) from the "bicycle" model described above that fit:

[0037] 4 also shows the presence of an observer element 26. This element 26 makes it possible to provide an estimate of the state of the vehicle 1. In practice, element 26 is connected to various digital sensors in the vehicle 1 and therefore receives all the measurements related to the vehicle 1.

[0038] Element 26 also receives from element 22 information sent by control unit 5 regarding routing control.

[0039] Element 26 then calculates the estimated data X est To this end, element 26 generates an estimated path for vehicle 1 using the vehicle 10. For this purpose, element 26 collects observed data L, which is a compilation of measurements on vehicle 1 and the variables estimated from these measurements that are necessary for the definition of the control law.P Generate the observation data L P is a function of the moving speed of vehicle 1.

[0040] In other words, the observation data L P is determined from the moving speed of the vehicle 1 involved. est In that case, the following equation is satisfied: TIFF2024526782000005.tif9170, L P is the gain value associated with the observer element 26.

[0041] As shown in Figure 4, the estimated data X est Then, the ideal path X ref The difference between the estimated path and the ideal path is processed by element 20, which determines a new control set point, e.g. the front wheel rotation angle δ req Component δ of FBK To this end, element 20 employs adjustment data Ks. The rotation angle δ of the front wheels is adapted to generate new control set points for req Component δ of FBK The new control set point for the estimated path X est and ideal path X ref The new control set point is then obtained by multiplying the difference between the set point and the adjustment data Ks. The new control set point is therefore a function of the adjustment data Ks. This adjustment data Ks is actually expressed in the form of a matrix.

[0042] The adjustment data Ks is a function of the speed of the vehicle 1. In other words, the control method shown in Figure 4 uses different values ​​of the adjustment data Ks, each of which is associated with a moving speed of the vehicle 1.

[0043] The values ​​of the calibration data Ks associated with each of the relevant travel speeds are determined when the vehicle 1 is designed. Their values ​​are therefore fixed before use of the vehicle 1. The rotation angle δ of the front wheels, generated from the calibration data Ks req Component δ of FBK The control setpoint for is therefore called predictive.

[0044] Figure 4 also shows the presence of a predictor element 24. This element 24 determines, among other things, the angle of rotation of the front wheels δ required to follow the lane. req Component δ of FFD It is possible to take into account the curvature of the lane by evaluating

[0045] Vehicle 1 is in the center of the turn ( tif7170) (y=0, y=0 and dδ / dt=0), the rotation angle δ of the front wheel determined by the predictor element 24. req Component δ of FFD The set points for are written in the following format: TIFF2024526782000007.tif8170 formula, L (unit: m) is the wheelbase of vehicle 1, ∇ SV is the understeer gradient specific to the vehicle 1 and defined by the following equation: TIFF2024526782000008.tif15170, M f and M. r (in kg) are the weights applied to the front and rear drivetrains of vehicle 1, respectively.

[0046] The predictor 24 is also connected to various digital sensors in the vehicle 1 and therefore receives all measurements relating to the vehicle 1 .

[0047] As FIG. 4 shows, in order for the vehicle 1 to navigate a turn with a known curvature ρ, the angle that should be applied to the steering wheel (and thus the angle set point δ req ) is finally divided into two components (δ FBK and δ FFD ) depending on δ req = δ FBK +δFFD

[0048] The invention therefore now relates to the angle to be applied to the steering wheel (and thus the angle set point δ to be transmitted to the wheel) in order for the vehicle 1 to move in a turn with a known curvature ρ. req The purpose of this Convention is to determine the

[0049] The computer 12 of the control device 10 (and more generally the control unit 5 ) is adapted to execute a method for controlling the path of the motor vehicle 1 .

[0050] The method executed by the computer 12 is adapted to control in real time the path of the motor vehicle 1 in a lane, in particular during turns, where the expression "real time" means that the path of the motor vehicle 1 can be controlled at regular intervals as the vehicle 1 moves in the lane.

[0051] To this end, computer 12 employs a method including several steps, which are described below.

[0052] The sequence of steps taken in the context of this method is depicted in flow chart form in FIG.

[0053] As Fig. 3 shows, the method starts in step E2, when the motor vehicle 1 starts to move out and move in the lane, where the autonomous lane following function is considered to be activated.

[0054] When activating this function, the rotation angle set point δ req To determine , the method comprises: SV_init Understeer gradient value from ∇ SV This includes a step E4 of initializing this predetermined value ∇ SV_init is, for example, a default value stored in the memory 14. This predetermined value ∇ SV_initare, for example, the weights M applied to the front and rear drive trains of the vehicle 1, respectively. f and M. r and the corresponding stiffness coefficient c f and c r It depends on the rotation angle δ req The set point generated by the control unit 5 for this predetermined value ∇ SV_init It is determined based on a predetermined value ∇ SV_init is, more precisely, the required rotation angle δ req Component δ of FFD In parallel with this, the observer element 26 determines the required rotation angle δ req The other component δ FBK The rotation angle set point at start-up δ req Therefore, the starting set point is obtained by summing these two components. This starting set point is then transmitted to the steering system of the motor vehicle 1.

[0055] The method then proceeds with steps E6 to E60, which are executed in a loop when the vehicle 1 is moving. These steps are more precisely executed for each successive sampling increment δt of a number of sampling increments δt of the time during which the motor vehicle 1 has been moving. This sampling increment δt is, for example, of the order of 10 milliseconds.

[0056] At the relevant sampling increment δt, during a step E6, the computer 12 detects whether the lane contains a turn.

[0057] To detect the presence of a turn in the lane, the computer 12 verifies at least the following conditions regarding the characteristic parameters of the movement of the motor vehicle 1. These parameters characterizing the movement are, for example, the angle of the front wheels, the yaw rate of the vehicle 1, the lateral rate of the vehicle 1, the lateral acceleration or the lateral offset of the vehicle 1. Alternatively, it can be based on data from the map and the navigation software.

[0058] Here, a turn is detected in particular if the angle of the front wheels, the yaw velocity of the vehicle 1 and the lateral velocity of the vehicle 1 have the same sign. Another condition for the detection of a turn concerns the absolute value of the lateral acceleration between a minimum threshold and a maximum threshold. The minimum threshold is, for example, 0.84 m / s 2 The maximum threshold is, for example, 1.5 m / s 2 This is the order.

[0059] A turn is also detected if the lateral offset is less than a predetermined value, for example less than 1 m.

[0060] A turn is initiated when the time derivative of the yaw rate is less than a given value for a period of time, e.g., 0.05 rad / s for 1 second. 2 It will also be detected if it is smaller than

[0061] This turn detection is only employed when the moving speed of the vehicle 1 is greater than a minimum moving speed threshold of the vehicle 1 and movement at low speeds is only marginally representative of the general movement behavior of the motor vehicle 1 in the lane.

[0062] If no turn is detected in step E6, i.e. if the vehicle 1 is driving on a straight part of the lane, the method continues to E8. During this step, the understeer gradient ∇ SV_δt is equal to a constant value, which may be, for example, a predetermined value ∇ SV_init Alternatively, this constant value may be the understeer gradient value determined for the previous sampling increment and stored in a database in memory 14 (the determination of which is described below).

[0063] As FIG. 3 shows, the method then includes a step E10, during which a rotation angle set point δ is determined (using the formula introduced above). req , and therefore the understeer gradient ∇ determined in step E8 in order to determine the control set point for the path of the motor vehicle 1. SV_δtThe predictor element 24 more specifically determines the required rotation angle δ req Component δ of FFD In order to determine the understeer gradient ∇ determined in step E8, SV_δt In parallel, the observer element 26 uses the required rotation angle δ req The other component δ FBK Estimate the rotation angle set point δ req Therefore, the set point is obtained by summing these two components. This set point is then transmitted to the steering system of the motor vehicle 1.

[0064] The sampling increment is then incremented to execute the steps of the method for the next sampling increment (as described above, the method is executed at regular intervals as the vehicle 1 is moving in the lane). The method therefore returns after this to step E6.

[0065] If, in step E6, the computer 12 detects that the vehicle 1 is traveling in a turn, the vehicle 1 therefore makes the detected turn and the method continues with step E20.

[0066] During this step, the computer 12 determines whether the vehicle 1 has been running in a lane for a predetermined duration τ app In other words, the computer 12 now evaluates whether the vehicle has traveled through one (or several) turns during this predetermined duration τ app τ , the vehicle is determined to have traveled in a turn (in one or more turns). app is, for example, greater than 30 seconds, for example, on the order of 50 seconds.

[0067] If this is not the case, the method continues to step E22, during which the computer 12 calculates, for the sampling increment concerned, a first quantity Φ(δt) associated with the understeer gradient. T.The value of Y(δt) and the second quantity Φ(δt) T .Determine the value of Φ(δt).

[0068] Equation (3) can be more specifically rewritten in the following form, with state variables Φ and Y characterizing the movement of the motor vehicle 1 within its lane: Y(δt)=Φ(δt).Θ(δt) During the ceremony, Θ(δt)=∇ SV , Y(δt)=δ req -ρL and Φ(δt)=ρv 2

[0069] It is then possible to isolate the understeer gradient by writing: Θ(δt)=(Φ(δt) T .Φ(δt) -1 .(Φ(δt) T Y(δt) During the ceremony... T is the notation for the transpose of a matrix, … -1 corresponds to the inverse of a matrix.

[0070] In practice, during the execution of the method according to the invention, the computer 12 optimizes the value of the understeer gradient, and therefore calculates, using the above formula, a first quantity Φ(δt) associated with the understeer gradient. T .Y(δt) and a second quantity Φ(δt) T .We seek to optimize Φ(δt).

[0071] In step E22, for the sampling increment δt concerned, the matrices Y(δt) and Φ(δt) are determined, and thus from the measured instantaneous values ​​of the characteristic parameters of the motor vehicle 1 (measurements obtained by various sensors in the vehicle 1). The characteristic parameters used are in particular the wheelbase of the vehicle 1, the lane curvature ρ and the travel speed v of the vehicle 1. It is noted, for example, that the lane curvature ρ is determined from the following formula: TIFF2024526782000009.tif14170

[0072] During this step, the rotation angle value δ req are values ​​obtained in open loop and measured at sampling increments δt by sensors associated with the motor vehicle 1.

[0073] The first quantity Φ(δt) T .Y(δt) and a second quantity Φ(δt) T .Φ(δt) is then determined based on the instantaneous values ​​of matrices Y(δt) and Φ(δt) for sampling increment δt by a recursive least squares method.

[0074] As shown in Figure 3, the method proceeds to step E24. During this step, the computer 12 calculates the first stored value Φ T .Y and a second stored value Φ T .Φ is stored in a database in memory 14.

[0075] The first stored value Φ T Y is the first quantity Φ(δt) determined for the sampling increment δt (step E22) T The second stored value Φ is a function of Y(δt) but also of the first quantity determined for the preceding sampling increment. T Similarly for Φ, the second stored value Φ T Φ is the second quantity Φ(δt) determined for the sampling increment δt (in step E22). T .Φ(δt) and also a function of a second quantity determined for the preceding sampling increment.

[0076] For example, the first (respectively second) stored value Φ T .Y(Φ T .Φ) corresponds to the sum of the first (respectively second) quantities determined for all of the sampling increments up to the current sampling increment.

[0077] In this case, the computer 12 actually calculates the sum of the first stored values ​​stored for the preceding sampling increments (which itself is obtained from the sum of the stored preceding first values) and the first quantity Φ(δt) determined for the current sampling increment δt. T .The result of the summation with Y(δt) is stored.

[0078] Alternatively, the stored first (respectively second) value Φ T .Y may correspond to the average of the first (respectively second) quantity determined for all of the sampling increments up to the current sampling increment.

[0079] For example, also here, when starting the motor vehicle 1, the first quantity Φ(δt) T .Y(δt) and a second quantity Φ(δt) T Φ(δt) is considered to be 0. The first stored value Φ determined at the first sampling increment during the turn T .Y and a second stored value Φ T .Φ therefore depends directly on the instantaneous values ​​of the matrices Y(δt) and Φ(δt) determined for this first sampling increment during the turn.

[0080] The method then continues to step E26, during which the computer 12 determines whether the motor vehicle 1 has exited the turn detected in step E6.

[0081] If this is not the case, ie if the motor vehicle 1 is still in the turn detected in step E6, the method returns to step E20.

[0082] On the other hand, if the motor vehicle 1 has exited the turn it was negotiating, the method continues with step E28, which therefore means that the motor vehicle 1 is now driving in a straight line.

[0083] During this step, the computer 12 calculates the component δ FFD (Thus, the rotation angle δreq The understeer gradient ∇ is used to determine the set point SV_δt_act It should therefore be noted here that the understeer gradient value is updated only when the motor vehicle 1 is traveling in a straight line (and therefore between two successive turns). The understeer gradient value is advantageously updated for each turn while the motor vehicle 1 is moving. This makes it possible in particular to prevent abrupt changes of the path control setpoints of the motor vehicle 1 during turns and thus to ensure the comfort of the occupants of the vehicle 1.

[0084] Here, the updated understeer gradient value ∇ SV_δt_act is determined in step E24, thus the first stored value Φ T .Y and the second stored value Φ T .Φ is a function of the understeer gradient. SV_δt_act More specifically, the first stored value Φ T .Y and the second stored value Φ T Φ is determined as the ratio between TIFF2024526782000010.tif14170

[0085] However, the learning period of the method is not considered to be over since in step E20 it was determined that the travel time of the vehicle 1 in one or more turns has not reached the predetermined duration τapp. SV_δt_act is not considered optimal and must therefore be corrected.

[0086] For this purpose, step E30 comprises the step of calculating the intermediate value ∇ SV_δt_int In order to determine the understeer gradient ∇ determined in step E28, SV_δt_act This is the step to correct the intermediate value of the understeer gradient ∇ SV_δt_int is the value of the understeer gradient determined in step E28, ∇SV_δt_act and the predetermined value ∇ used in the initialization step E4. SV_init In other words, when little turn data is acquired, an adjustment factor is applied to limit the understeer gradient value estimation error. app This adjustment during the learning period then allows for linear and gradual convergence of the understeer gradient value to enable the generation of the most constant and fluid possible control point (without rocking felt by the occupants of vehicle 1).

[0087] The method then continues with step E32 of determining a first acceleration value and a further second acceleration value of the vehicle 1 for the sampling increment concerned, where for example the acceleration is the lateral acceleration of the vehicle 1 and the further acceleration is the lateral acceleration of the vehicle 1. The computer 12 then determines the difference between the first acceleration and the second acceleration.

[0088] In step E34, this difference is compared with a predefined acceleration threshold which makes it possible to identify possible understeer gradient estimation errors, such as may be observed when loading the motor vehicle 1 heavily or in the case of so-called sharp turns (where the lateral acceleration will be high), where this predefined acceleration threshold takes the form of, for example, a map which may, for example, determine that the difference between the first and second accelerations is approximately 0.2 m / s 2 If it is smaller than a given threshold, the median value of the understeer gradient ∇ SV_δt_int indicates that no correction is applied to the final value of the understeer gradient ∇ SV_δt_fin Therefore, the median value of the understeer gradient ∇ SV_δt_int (step E36a).

[0089] However, if the difference between the first acceleration and the second acceleration is about 0.2 m / s 2 If the mean value of the understeer gradient ∇ is greater than this predetermined threshold, SV_δt_intis corrected by a correction value which is added to this intermediate value (step E36b). This correction value is given, for example, by the map mentioned above. For example, if the difference between the first acceleration and the second acceleration is 1 m / s 2 If it is greater than 1.7×10, the understeer gradient correction value is 1.7×10 -3 rad.s 2 / m. The final value of the understeer gradient is ∇ SV_δt_fin Therefore, the median value of the understeer gradient ∇ SV_δt_int and the correction value described above added thereto.

[0090] The computer 12 then calculates the final value of the understeer gradient ∇ SV_δt_fin Using the formula introduced above, we obtain the rotation angle set point δ req , and therefore the route control setpoints for the motor vehicle 1 are determined (step E38).

[0091] In a manner similar to that described for step E10 introduced above, the predictor element 24 determines, more precisely, the required rotation angle δ req Ingredients FFD In order to determine the final value of the understeer gradient ∇ obtained in step E36a or E36b SV_δt_fin In parallel, the observer element 26 uses the required rotation angle δ req Other components of δ FBK Estimate the rotation angle δ req The set point is therefore obtained by summing these two components. This set point is then transmitted to the steering system of the motor vehicle 1.

[0092] The sampling increment is then incremented to execute the steps of the method for the next sampling increment (as described above, the method is executed at regular intervals as the vehicle 1 moves in the lane). The method therefore returns after this to step E6.

[0093] In step E20, the vehicle 1 is determined to be in a lane for at least a predetermined duration τ app If the computer 12 determines that the vehicle has traveled through one (or more) turn(s) for a duration equal to E40, the method continues to E40.

[0094] During this step E40, the computer 12 calculates the total duration τ of the trip in one or more turns since the last update of the database. tot Determine whether Here, the total duration τ tot is greater than 50 seconds.

[0095] Total duration τ tot is, for example, a predetermined duration τ app is proportional to the given duration τ app If is 50 seconds, the total duration τ tot For example, the predetermined duration τ app If is 30 seconds, the total duration τ tot is 70 seconds.

[0096] The total duration τ of the run in the turn since the last update of the database tot If this is not the case, the method continues with steps E42 and E44, similar to steps E22 and E24, respectively, described above. Following step E44, the computer 12 therefore determines the first stored value Φ T .Y and a second stored value Φ T .Φ are stored in a database in memory 14, these values ​​being obtained from measurements taken for the current sampling increment δt.

[0097] As in E26 described above, the computer 12 determines in step E46 whether the motor vehicle 1 has exited the turn detected in step E6.

[0098] If this is not the case, ie if the motor vehicle 1 is still negotiating the turn detected in step E6, the method returns to step E20.

[0099] On the other hand, if the motor vehicle 1 has exited the turn it was negotiating, the method continues with step E48, which therefore means that the motor vehicle 1 is now driving in a straight line.

[0100] During this step E48, the computer 12 calculates the component δ FFD The understeer gradient value ∇ used to determine SV_δt_act Update the value of

[0101] As FIG. 3 shows, once this value of the understeer gradient value has been updated, the method continues by calculating the understeer gradient value ∇ obtained in step E48 in a manner similar to that described above for steps E32, E34, E36a and E36b, respectively. SV_δt_act From the updated value of , steps E50, E52, E54a and E54b follow, which make it possible to determine the final value of the understeer gradient.

[0102] Then, in step E56, the computer 12 determines (in a similar manner to step E38 described above) this final value of the understeer gradient (corrected or not corrected by the correction value) ∇ SV_δt_fin Using the formula introduced above, we obtain the rotation angle set point δ req , thus determining the route control setpoint for the motor vehicle 1.

[0103] The sampling increment is then incremented to execute the steps of the method for the next sampling increment (as described above, the method is executed at regular intervals when the vehicle 1 is moving in the lane). The method therefore returns after this to step E6.

[0104] In step E40, the total duration τ of the trip in the turn since the last update of the database is calculated. tot If this has been reached, the method continues to step E60, during which the database is updated.

[0105] At the start of step E60, the database is checked for the first stored value Φ determined for the previous sampling increment. T .Y and a second stored value Φ T Remember .Φ.

[0106] During step E60, the computer 12 therefore calculates the first stored value Φ T .Y and a second stored value Φ T .Update each of Φ.

[0107] In practice, the computer 12 first stores the first stored value Φ T .Y (respectively the second stored value Φ T The coefficient of the proportionality to be applied is, for example, a given duration τ app and the total duration τ tot It is a function of the ratio of

[0108] For example, for a given duration τ app is equal to 50 seconds, and the total duration τ tot In the situation where Φ is equal to 100 seconds, the coefficient of proportionality applied is 1 / 2. The first intermediate value (respectively the second intermediate value) is therefore the first stored value Φ T .Y / 2 (respectively the second stored value Φ T .It is equal to 1 / 2 Φ.

[0109] In step E60, the first stored value Φ T .Y and a second stored value Φ T Φ are thus updated (by overwriting them) with the first and second intermediate values, respectively. T.Y" and "Second stored value Φ T .Φ" is therefore retained after step E60.

[0110] As FIG. 3 shows, the method then returns to step E40.

Claims

1. A method for controlling the path of a motor vehicle (1) traveling in a lane, comprising: detecting a turn in the lane, and then, when the motor vehicle (1) enters the turn, Based on state variables (Φ, Y) characterizing the movement of the motor vehicle (1), a first quantity (Φ(δt) Ｔ .. Y(δt)) and a second quantity (Φ(δt) Ｔ .. Φ(δt)) are determined; The step of determining a first stored value (Φ Ｔ .Y) and a second stored value (Φ Ｔ .Φ), wherein the first stored value (Φ Ｔ .Y) is a function of the first quantity (Φ(δt) Ｔ .Y(δt)) determined for the current sampling increment and the first quantity determined for at least one of the preceding sampling increments, and the second stored value (Φ Ｔ .Φ) is a function of the second quantity (Φ(δt) Ｔ .Φ(δt)) determined for the current sampling increment and the second quantity determined for at least one of the preceding sampling increments; a step of determining a first stored value (Φ Ｔ .Y) and a second stored value (Φ Ｔ .Φ); The first stored value (Φ Ｔ ..Y) and the second stored value (Φ Ｔ ..Φ) determined for each sampling increment (δt) are stored in a memory, and then, when the motor vehicle (1) exits the turn, The first stored value (Φ Ｔ .Y) stored in the memory and the second stored value (Φ Ｔ .Φ) as a function to determine the value of the understeer gradient (∇ ＳＶ＿δｔ＿ａｃｔ ) Determining a command for the motor vehicle (1) based on the determined value of the understeer gradient (∇ ＳＶ＿δｔ＿ａｃｔ ) A method including.

2. The first stored value (Φ Ｔ .Y) is a function of the sum of the first quantity (Φ(δt) Ｔ .Y(δt)) determined for the current sampling increment and the first quantity determined for at least one of the preceding sampling increments, and the second stored value (Φ Ｔ .Φ) is a function of the sum of the second quantity (Φ(δt) Ｔ .Φ(δt)) determined for the current sampling increment and the second quantity determined for at least one of the preceding sampling increments, the method according to claim 1.

3. The state variables (Φ, Y) characterizing the movement of the motor vehicle (1) are components of the rotation angle of the wheels of the motor vehicle (1) (δ ＦＦＤ ), the curvature of the lane, the travel speed (v) of the motor vehicle (1), or a function of the wheelbase (L) of the motor vehicle (1), according to the method of claim 1 or 2.

4. The method according to claim 1 or 2, wherein the step of determining the value of the understeer gradient is performed for each turn negotiated by the motor vehicle (1).

5. correcting the value of the understeer gradient to determine an intermediate value (∇ ＳＶ＿δｔ＿ｉｎｔ ) of the understeer gradient, the intermediate value (∇ ＳＶ＿δｔ＿ｉｎｔ ) of the understeer gradient being determined based on a weighting between the determined value of the understeer gradient (∇ ＳＶ＿δｔ＿ａｃｔ ) and a predetermined value, the method according to claim 1 or 2.

6. The value of the understeer gradient (∇ ＳＶ＿δｔ＿ａｃｔ ) is determined based on the ratio between the first stored value (Φ Ｔ .Y) and the second stored value (Φ Ｔ .Φ), the method according to claim 1 or 2.

7. determining a first acceleration value and another second acceleration value of the motor vehicle; determining a difference between the first acceleration value and the other second acceleration value; when the determined difference is greater than a predetermined threshold, further correcting the value of the understeer gradient based on a correction value that is a function of the determined difference The method according to claim 1 or 2, further comprising.

8. The detection of the turn depends on parameters characterizing the movement of the motor vehicle (1), at least some of the parameters being selected from the angle of the front wheels of the motor vehicle (1), the yaw rate of the motor vehicle (1), the lateral offset between the center of gravity (G) of the motor vehicle (1) and the ideal path, the lateral acceleration of the motor vehicle (1), or the speed of movement of the motor vehicle (1). The method according to claim 1 or 2.

9. Said first quantity (Φ(δt) Ｔ ·Y(δt)) and said second quantity (Φ(δt) Ｔ ·Φ(δt)) are determined using the recursive least squares method as a function of state variables (Φ, Y) characterizing said movement of said motor vehicle (1), method according to claim 1 or 2

10. The step of determining the command for the motor vehicle (1) includes a sub-step of determining a component (δ ＦＦＤ ) of the rotation angle of a wheel of the motor vehicle (1), according to the method of claim 1 or 2.

11. A device (10) for controlling the path of a motor vehicle (1) traveling in a lane, comprising a computer (12) and a memory (14) provided with a database having a finite number of locations, the computer (12) being detecting a turn in the lane, and then, when the motor vehicle (1) enters the turn, Based on state variables (Φ, Y) characterizing the movement of the motor vehicle (1), a first quantity (Φ(δt) Ｔ . Y(δt)) and a second quantity (Φ(δt) Ｔ . Φ(δt)) are determined, and Determining a first stored value (Φ Ｔ .Y) and a second stored value (Φ Ｔ .Φ), wherein the first stored value (Φ Ｔ .Y) is a function of the first quantity (Φ(δt) Ｔ .Y(δt)) determined for the current sampling increment and the first quantity determined for at least one of the preceding sampling increments, and the second stored value (Φ Ｔ .Φ) is a function of the second quantity (Φ(δt) Ｔ .Φ(δt)) determined for the current sampling increment and the second quantity determined for at least one of the preceding sampling increments, determining a first stored value (Φ Ｔ .Y) and a second stored value (Φ Ｔ .Φ); For each sampling increment (δt), the determined first stored value (Φ Ｔ .Y) and the second stored value (Φ Ｔ .Φ) are stored in memory, and then, when the motor vehicle (1) exits the turn, the first stored value (Φ Ｔ .Y) stored in the memory and the second stored value (Φ Ｔ .Φ) as a function to determine the value of the understeer gradient (∇ ＳＶ＿δｔ＿ａｃｔ ) Determining a command for the motor vehicle (1) based on the determined value of the understeer gradient (∇ ＳＶ＿δｔ＿ａｃｔ ) A device (10) designed to perform.

12. A motor vehicle (1) including a powertrain, a steering system, and a device (10) for real-time path control according to claim 11 adapted to control the steering system.

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