Method for characterizing trackside lines for the purpose of controlling a motor vehicle

Abstract

The invention relates to a method for controlling a motor vehicle (10) traveling on a traffic lane (31) of a road (30), comprising steps of: - characterizing edge lines (33, 35) of said traffic lane in a local reference frame (Rveh) attached to the vehicle, - calculating a control instruction for the motor vehicle as a function of said edge lines, and - controlling a steering actuator of said motor vehicle according to said control instruction. According to the invention, during the characterization step, it is provided: - to characterize the edge lines in a global reference frame (R0) stationary relative to the traffic lane, then - to perform on the edge lines identified in the global reference frame a calculation of a change of reference frame to the local reference frame. Figure for the abstract: Fig.1

Description

Title of the invention: Method for characterizing trackside lines for the purpose of controlling a motor vehicle Technical field of the invention

[0001] The present invention relates generally to driving aids for motor vehicles.

[0002] The invention relates more specifically to a method for controlling a motor vehicle traveling on a traffic lane of a road, comprising steps of: - characterizing edge lines of said traffic lane in a mobile local reference frame attached to the motor vehicle, - calculation, by a computer on board said motor vehicle, of a steering instruction for the motor vehicle based on said edge lines identified in said local reference system, and - control by the computer of a steering actuator of said motor vehicle according to said control instruction.

[0003] The invention also relates to a motor vehicle suitable for implementing such a method. It applies more particularly to cars and other motorized vehicles traveling on roads. State of the art

[0004] In an effort to make motor vehicles safer, they are currently being equipped with driving assistance functions and even highly automated driving functions.

[0005] These are typically centering or lane centering functions (better known respectively by the English acronym LCA for “Lane Centering Assist” or LKA for “Lane Keeping Assist”).

[0006] A centering function (hereinafter referred to as the "LCA function") needs, in order to operate, to know the position of the edges of the traffic lane taken by the vehicle. Currently, it is known to use a sensor, such as a camera, which incorporates image processing means in order to determine the position of each of the lane edge marking lines in the vehicle's reference frame.

[0007] A computer on board the vehicle can then deduce the position of the center line of the traffic lane taken, which then allows it to automatically control the vehicle so that the latter follows this center line.

[0008] It is understood that the detection of the edges of the traffic lane must be extremely reliable to prevent the vehicle from leaving this lane.

[0009] Unfortunately, this detection is not always entirely satisfactory. For example, it happens that a turn, a widening or a narrowing of the lane is detected late. This delay can then lead to approving an inappropriate decision to change trajectory. It is then understood that the motor vehicle cannot be piloted in the desired conditions of comfort and safety. Presentation of the invention

[0010] In order to overcome the aforementioned drawback of the state of the art, the present invention proposes a new method for detecting trackside lines.

[0011] More particularly, according to the invention, a method is proposed as defined in the introduction, in which, during the step of characterizing these edge lines, it is provided to: - characterize the edge lines of said traffic lane in a global reference frame stationary relative to the traffic lane, then - perform a calculation of the change of reference to the local reference on the edge lines identified in the global reference system.

[0012] Thus, the invention proposes to detect the track edge lines in a stationary frame of reference rather than in a frame of reference attached to the motor vehicle.

[0013] Thanks to this characteristic and surprisingly, it is possible to detect more quickly, at least under certain conditions, turns or other changes in the shape of the traffic lane, which will allow better choices to be made in terms of trajectories to follow.

[0014] Other advantageous and non-limiting characteristics of the method according to the invention, taken individually or in all technically possible combinations, are the following: - to characterize the edge lines of said traffic lane in the global reference frame, it is planned to determine a trajectory of the motor vehicle in the global reference frame then to position the motor vehicle on said trajectory, and then to evaluate the positions of the edge lines in relation to said trajectory; - said trajectory is defined on the curvilinear abscissa; - the said trajectory is defined with a step between 0.1 and 2 meters, and over a length between 50 and 200 meters; - to evaluate the positions of the edge lines relative to said trajectory, it is planned to acquire the distance between each edge line and the trajectory at several points of the trajectory; - each edge line of said traffic lane identified in the local reference system is modeled by a polynomial equation; - the polynomial equation of each boundary line is of order three and has four coefficients associated with a position, a heading angle, a curvature and a curvature derivative of said edge line; - prior to the calculation step, it is planned to characterize a center line of said traffic lane as a function of the edge lines of said traffic lane identified in the local reference system, and, during the calculation step, the piloting instruction is calculated as a function of the center line.

[0015] The invention also provides a motor vehicle comprising: - acquisition means adapted to acquire, when the motor vehicle is moving on a traffic lane, data relating to the edge lines of said traffic lane, - a steering actuator adapted to control the motor vehicle, and - a computer programmed to implement a control method as mentioned above.

[0016] Of course, the various features, variants and embodiments of the invention may be combined with each other in various combinations to the extent that they are not incompatible or mutually exclusive. Detailed description of the invention

[0017] The description which follows with reference to the appended drawings, given as non-limiting examples, will make it clear what the invention consists of and how it can be implemented.

[0018] In the attached drawings:

[0019] [Fig-1] is a schematic perspective view of a motor vehicle which is adapted to implement a piloting method in accordance with the invention and which runs on a traffic lane of a road;

[0020] [Fig.2] is a diagram illustrating steps in implementing the control method according to the invention;

[0021] [Fig.3] represents three graphs which illustrate the variations over time of three parameters used in the context of the control method according to the invention.

[0022] In [Fig. 1], a motor vehicle 10 is shown which is suitable for implementing the invention.

[0023] This is a car. Alternatively, it could be another type of vehicle (truck, motorcycle, etc.).

[0024] In this figure, the motor vehicle 10 is traveling on a traffic lane 31 of a road 30. It can be seen that the road 30 has in this example two lateral marking lines 34, 35 (which delimit it) and a central marking line 33 delimiting two traffic lanes 31, 32.

[0025] A traffic lane is herein defined as the part of a road on which a Only one vehicle at a time is allowed to travel abreast. Such a traffic lane is usually demarcated between marking lines.

[0026] A road (or roadway) is defined as a set of traffic lanes. In the example considered here for illustrative purposes, this road 30 therefore comprises two traffic lanes 31 on which vehicles can travel in opposite directions.

[0027] The center line of the taxiway will be defined as the geometric curve extending along the center of the taxiway 31, equidistant from the two lateral marking lines 34, 35.

[0028] As shown in [Fig.l], the motor vehicle 10 conventionally comprises a chassis, front wheels 13, steered and rear wheels 14, here non-steered, and a passenger compartment in which there is in particular a seat for the driver 40 of the vehicle and a steering wheel 12.

[0029] This motor vehicle 10 conventionally comprises a powertrain, a braking system and a steering system for turning the vehicle. Conventionally, the steering system comprises an electronically controllable power steering actuator, the powertrain comprises an electronically controllable engine control actuator, and the braking system comprises an electronically controllable braking actuator.

[0030] The motor vehicle 10 further comprises an electronic and / or computer processing unit (hereinafter called computer 11) comprising at least one microprocessor, at least one memory and input and output interfaces.

[0031] Thanks to its input interfaces, the computer 11 is adapted to receive different input data which come from sensors or third-party computers.

[0032] Among these sensors, for example, a front camera is provided for locating the edges of the traffic lane 31 being used. Sensors are also provided that are suitable for determining the values ​​of other parameters relating, for example, to the position of the vehicle in its traffic lane, to the traffic lane and to the dynamics of the vehicle.

[0033] Thanks to its output interfaces, the computer is adapted to control the power steering actuator, the engine control actuator, and the braking actuator.

[0034] Thanks to its memory, the computer stores a computer application, consisting of computer programs comprising instructions whose execution by the computer allows the implementation of a function for automatically keeping the vehicle in the center of its traffic lane (hereinafter called the LCA function), and more generally of the method described below.

[0035] The LCA function, in order to operate, must receive as input the positions and shapes of the right and left track edge lines, in order to deduce the positions and shapes of the center line of traffic lane 31 which must be followed.

[0036] It will be noted that the lane edge lines will preferably be formed by the ground marking lines 33, 35. In the absence of these marking lines, they could be formed by the edge of the roadway, a safety barrier, a sidewalk, etc.

[0037] Within the framework of the LCA function, these edge lines 33, 35 must be characterized by parameters of equations representative of their shapes and their positions, expressed in a reference frame attached to the motor vehicle.

[0038] According to the invention, these edge lines 33, 35 will be characterized not directly in this local reference frame attached to the motor vehicle 10 (which is mobile), but in a stationary global reference frame. They will then preferably be identified relative to the trajectory T1 of the motor vehicle.

[0039] To illustrate these reference frames, [Fig. 1] shows an orthogonal reference frame attached to the motor vehicle 10, which is called the vehicle reference frame Rveh (CG, Xveh, Yveh, Zveh) and which is associated with the aforementioned local reference frame. Its origin is the same as the center of gravity CG of the motor vehicle 10. The Xveh axis corresponds to the longitudinal axis of the vehicle. The Yveh axis corresponds to the lateral axis facing towards the left of the vehicle. When the vehicle is traveling on a horizontal road, the Zveh axis corresponds to the vertical axis. More generally, this Zveh axis is the axis normal to the road. This reference frame is described as mobile since it moves in the terrestrial reference frame (it is mobile relative to the road 30).

[0040] Also shown in this [Fig.l] is a stationary orthogonal reference frame, which is called the global reference frame R0 (0, XR0, YR0, ZR0) and which is associated with the aforementioned global reference frame. Its origin could be positioned in any way. For ease of calculation, it is in practice merged with the center of gravity CG of the motor vehicle 10 at an initial time step t0. More generally, this global reference frame R0 is merged with the vehicle reference frame Rveh at the initial time step t0. This reference frame is described as stationary since it does not move in the terrestrial reference frame during the implementation of the method described below (it is stationary relative to the road).

[0041] To summarize, the edge lines 33, 35 will then be defined relative to the trajectory T1 of the motor vehicle defined not in the vehicle frame Rveh but in the global frame R0. Then, thanks to a frame change matrix, it will be possible to make a polynomial identification of the edge lines 33, 35 on a certain horizon in the vehicle frame Rveh.

[0042] We can then describe these different operations in more detail.

[0043] For this, during a preliminary operation OpO ([Fig.2]) implemented at the step of initial time to, the computer 11 begins by constructing the trajectory Tl of the motor vehicle 10 on the curvilinear abscissa in the global reference frame R0.

[0044] To do this, it begins by acquiring data to construct this trajectory T1. This data could be varied. It could be data from images captured by the camera, geolocation data, data relating to the dynamics of the vehicle (speed, acceleration), etc.

[0045] The curvature of the curvilinear abscissa is then determined taking into account these data.

[0046] It is then planned to define several points P; regularly distributed on the curvilinear abscissa. Then, each point P; on the curvilinear abscissa will represent the algebraic measure of an arc OP;.

[0047] The coordinates of the points P; of the trajectory Tl are calculated automatically, taking into account a step As chosen for the curvilinear abscissa and the curvature of the trajectory TL

[0048] Here, the curvilinear abscissa is defined over several tens of meters, for example over 100 meters. The step As chosen is preferably less than two meters. Here it is less than one meter and more precisely equal to fifty centimeters. In other words, the curvilinear abscissa is defined by two hundred points separated two by two by fifty centimeters.

[0049] Here, this step is therefore fixed. Alternatively, it could be provided that the step is chosen taking into account data such as the speed of the vehicle, the curvature of the trajectory Tl, etc.

[0050] The coordinates of the points P; then form a vector of points P; of the curvilinear abscissa.

[0051] After having constructed this vector, the calculator 11 determines by an interpolation calculation the curvature p; of the trajectory Tl at the level of the points P;.

[0052] Then, it determines the heading angle 0; of the trajectory Tl at each point Pi using the mathematical formula:

[0053] [Math.l]

[0054] In this equation: 0O = 0(to) = 0 since at the start of the process, at time step t0, the two reference points considered are the same.

[0055] The computer 11 can thus construct a vector of heading angles 0; of the trajectory TL

[0056] From then on, the computer 11 can determine the coordinates (xi5 y;) of the points P; of the trajectory Tl expressed in curvilinear abscissa in the global reference frame R0, using the mathematical formula:

[0057] [Math.2] ( Xf = Xj.j + [ j. = +

[0058] At this stage, the trajectory T1 that the motor vehicle 10 follows is well defined by: - ​​the vector of the curvilinear abscissas of the points P;, - the vector of the abscissas x; of these points in the global reference frame R0, and - the vector of the ordinates y; of these points in the global reference frame R0.

[0059] Once this preliminary operation has been completed, and while the motor vehicle 10 progresses along the road 30, the computer implements operations Op1 and following to characterize the edge lines 33, 35 of the traffic lane.

[0060] These operations are implemented in loops. We can describe how this process is executed at a time t, after the initial time t0.

[0061] The first operation Opl, shown in [Fig.2], consists of determining the position of the motor vehicle 10 (and more precisely that of its center of gravity CG) relative to its trajectory Tl.

[0062] To understand how this first operation Opl is implemented, it can first be noted that the LCA function, once the center line has been defined, can be executed by the computer using a model such as that defined in document FR3082162. Thus, at each time step, the model used will give the coordinates (xveh / Ro, yVeh / Ro) of the position of the motor vehicle 10 in the global reference frame R0, as well as its heading angle <bVeh / Ro- On notera qu’en variante, ces données pourraient être obtenues différemment (via le logiciel de navigation par exemple).

[0063] In practice, the position of the motor vehicle 10 at time t is not necessarily located on the trajectory T1 which had been constructed at time to, due to calculation errors, lack of precision, change of trajectory of the vehicle, etc.

[0064] We therefore seek the point P; of the trajectory Tl which is closest to the center of gravity CG of the motor vehicle 10.

[0065] In this case, we are looking for the index i of the point P; of the curvilinear abscissa which is closest to the point with coordinates (xveh / R0, yveh / Ro) - A smaller distance calculation can be used in this regard. Other methods are also possible as a variant.

[0066] The calculator thus obtains the approximate coordinates, noted (xveh / ROji, yVeh / Ro,i), of the position of the motor vehicle 10 on the trajectory TL

[0067] At this stage, it is planned to determine the coordinates (xL / R0>i, yL / Ro,i) of points characterizing the shape of the left edge line 33, and the coordinates (xR / R0>i, yR / R0,i) of points characterizing the shape of the right edge line 35, in the global reference frame R0.

[0068] For this, during a second operation Op2, the calculator determines, using an interpolation calculation, the positions of these edge lines 33, 35 relative to the points P; of the curvilinear abscissa vector.

[0069] More precisely, the calculator determines the lateral deviations dieft>i, dright>i of these two edge lines 33, 35 (along the YR0 axis) relative to the trajectory Tl. To do this, it can for example rely on the images acquired by the camera.

[0070] Then, it calculates the coordinates (xL / R0>i, yL / Ro,i) and (x^oj, y^oj) of the points of the right and left edge lines 33, 35 in the global reference frame R0 using the following equations.

[0071] [Math.3] ' XL / Roj^Xi-d^S^) ^L / R0,i — xR / R0,i= xi + right,i-sin(9z) ^R / R0,i —

[0072] He thus obtains the coordinates of points characterizing the shapes and positions of the edge lines 33, 35 right and left over a length of 100 meters.

[0073] It will be noted here that, taking into account the definition of the trajectory T1, the points characterizing these edge lines will also be spaced two by two by a distance substantially equal to the step As.

[0074] Alternatively, one could characterize not one edge line on the right and another edge line on the left, but two edge lines on each side of the vehicle. In practice, the lines will generally be merged in pairs. However, in the event of road widening (if the traffic lane taken divides into two traffic lanes) or road narrowing (if the traffic lane taken joins another traffic lane), it will be possible to detect this change in road shape. A selection function will then make it possible to choose one of the two lines in order to construct the center line.

[0075] At this stage, it is necessary, taking into account the software architecture of the LCA function, to express the future positions of the right and left edge lines 33, 35 in the vehicle reference frame Rveh. This LCA function has in fact been developed to receive these positions in this reference frame.

[0076] To do this, during a third operation Op3, the calculator performs a reference change calculation.

[0077] Before describing how, we can then introduce the following notations.

[0078] The coordinates of the points of the left edge line expressed in the reference frame- vehicle Rveh will be noted (xL / Rveh>i, yL / Rveh,i).

[0079] The coordinates of the points of the straight edge line expressed in the vehicle frame Rveh will be noted (xR / Rveh>i, y^vehj)-

[0080] We will note T the rotation matrix allowing to pass from the global reference frame R0 to the vehicle reference frame Rveh, which will be expressed in the form:

[0081] [Math.4] cosftb sin(d> X^veh / Rw \^veh / RW -sin((|) , / tJ co^(|) X^veh / RilJ \ rveh / R\J / J

[0082] Then the change of reference can be done using the following equation:

[0083] [Math.5] *L / Rvehj Y LIRvehj ^RjRvehi YR / Rvefù

[0084] The fourth operation Op4 then consists, for the computer 11, in determining the equation of the right and left edge lines 33, 35 in the vehicle reference frame Rveh, so that the LCA function can then be implemented.

[0085] These equations are here polynomials, preferably of order 3.

[0086] Each of these polynomials is therefore written in the following form:

[0087] [Math.6] y = cQ + cpc + c2^2 + c^x3

[0088] This interpolation calculation can typically be performed using Matlab's "polyfit" function.

[0089] Conventionally, this interpolation can be done taking into account the point cloud (xu Rvehj, yL / Rvehj) or (xR / Rveh>i, yR / RVeh,i), for example by a least squares method.

[0090] It will then be observed that the characteristics of the edge line at the level of the center of gravity CG of the motor vehicle 10 can be calculated from the coefficients thus identified.

[0091] More precisely, the position of the edge line at the vehicle will be equal to -c o. The heading angle of the edge line at the vehicle will be equal to -Cp The curvature of the edge line at the vehicle will be equal to 2.c2. The derivative of the curvature of the edge line at the vehicle will be equal to 6.c3.

[0092] Then, when the computer has determined the positions and shapes of the track edge lines 33, 35, it can implement the LCA function by: - determining an equation representing the center line of the traffic lane (the one located between the two right and left edge lines), - determining a steering instruction allowing the vehicle to follow this center line, and in - transmitting this instruction to the power steering actuator.

[0093] These three steps being well known to those skilled in the art, they will not be described here in more detail.

[0094] In [Fig. 3], an example of variation in time (t) of parameters is shown illustrating to what extent the present invention makes it possible to obtain reliable results and in advance compared to a conventional process in which the edge lines 33, 35 of the track are detected in the vehicle reference frame without passing through a global reference frame.

[0095] This example corresponds to a sharp turn, along a short clothoid, taken by the vehicle at 90 km / h, thus imposing a lateral acceleration of 0.2G.

[0096] The first graph represents the heading angle of one of the edge lines 33, 35, obtained using the method according to the invention (curve C0) and obtained using a method as used in the prior art (curve C0'). It can be seen that the variation in heading angle of the lane edge line is detected approximately one second earlier with the invention. In other words, the invention makes it possible to anticipate the entry and exit of the bend by one second.

[0097] The second graph represents the curvature of one of the edge lines 33, 35, obtained using the method according to the invention (curve C1) and obtained using a method as used in the prior art (curve C1'). The third graph represents the derivative of the curvature of one of the edge lines 33, 35, obtained using the method according to the invention (curve C2) and obtained using a method as used in the prior art (curve C2'). The same thing is still observed on these two graphs.

[0098] It will be noted here that if the difference between the results obtained with the invention and with the method of the prior art are very significant, this difference may not always be as marked depending on the configuration of the road. However, the strategy proposed by the invention will always make it possible to obtain results at least as good as those obtained in the prior art, or even significantly better.

[0099] It will also be noted that in the event of road widening, the invention will make it possible to detect very early on that one of the lane edge lines 33, 35 is moving away from the other, which will allow the computer to control the vehicle so that it remains in the center of its traffic lane, without moving towards this widening. This will also make it possible to avoid triggering inappropriate maneuvers, such as overtaking, before arriving at such a widening.

[0100] The present invention is in no way limited to the embodiment described and shown, but those skilled in the art will be able to provide any variant in accordance with the invention.

[0101] Typically, it can be applied to any other automated control function of the vehicle, in particular to the LKA function of keeping the vehicle between the edges of its traffic lane or to an obstacle avoidance function (in which we wish to know the characteristics of all the road marking lines).

Claims

Claims

1. Method for controlling a motor vehicle (10) traveling on a traffic lane (31) of a road (30), comprising steps of: - characterizing edge lines (33, 35) of said traffic lane (31) in a local reference frame (Rveh) mobile and attached to the motor vehicle (10), - calculating, by a computer (11) on board said motor vehicle (10), a control instruction for the motor vehicle (10) as a function of said edge lines (33, 35) identified in said local reference frame (Rveh), and - controlling by the computer (11) a steering actuator of said motor vehicle (10) according to said control instruction, characterized in that, during the characterization step, it is provided: - to characterize the edge lines (33, 35) of said traffic lane (31) in a global reference frame (R0) stationary relative to the traffic lane (31), then - to perform on the edge lines (33,35) located in the global reference frame (R0) a calculation of change of reference frame towards the local reference frame (Rveh)-,

2. A driving method according to claim 1, in which, to characterize the edge lines (33, 35) of said traffic lane (31) in the global reference frame (R0), it is provided to determine a trajectory (Tl) of the motor vehicle in the global reference frame (R0) then to position the motor vehicle (10) on said trajectory (Tl), and then to evaluate the positions of the edge lines (33, 35) relative to said trajectory (Tl).

3. Piloting method according to claim 2, in which said trajectory (Tl) is defined on the curvilinear abscissa.

4. A piloting method according to claim 3, wherein said trajectory (Tl) is defined with a step (As) of between 0.1 and 2 meters, and over a length of between 50 and 200 meters.

5. Piloting method according to claim 3 or 4, in which, to evaluate the positions of the edge lines (33, 35) relative to said trajectory (Tl), it is provided to acquire the distance (dieftji, dright>i) between each edge line (33, 35) and the trajectory (Tl) at several points (P;) of the trajectory (Tl).

6. A control method according to one of claims 1 to 5, in which each edge line (33, 35) of said traffic lane (31) located in the local reference frame (Rveh) is modeled by a polynomial equation.

7. A piloting method according to claim 6, wherein the polynomial equation of each edge line (33, 35) is of order three and comprises four coefficients (c0, cb c2, c3) associated with a position, a heading angle, a curvature and a derivative of curvature of said edge line (33, 35).

8. A driving method according to one of claims 1 to 7, in which, prior to the calculation step, provision is made to characterize a center line of said traffic lane (31) as a function of the edge lines (33, 35) of said traffic lane (31) identified in the local reference system (Rveh), and, during the calculation step, the driving instruction is calculated as a function of the center line.

9. Motor vehicle (10) comprising: - acquisition means adapted to acquire, when the motor vehicle (10) is moving on a traffic lane (31), data relating to edge lines (33, 35) of said traffic lane (31), and - a steering actuator adapted to control the motor vehicle (10), characterized in that it further comprises a computer (11) programmed to implement a control method in accordance with one of claims 1 to 8.

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