EP3999997A1

EP3999997A1 - On-board driving assistance method and device with plotting of the travelled lane contour

Info

Publication number: EP3999997A1
Application number: EP20730427.0A
Authority: EP
Inventors: Bruno DURAND; Chrysanthi PAPAMICHAIL
Original assignee: Renault SAS; Nissan Motor Co Ltd
Current assignee: Ampere Sas; Nissan Motor Co Ltd
Priority date: 2019-07-16
Filing date: 2020-06-08
Publication date: 2022-05-25
Also published as: FR3098778A1; CN114762011A; WO2021008775A1; FR3098778B1

Abstract

The invention concerns an on-board driving assistance device and method for a vehicle (VEH) comprising: - a step of detecting a lane contour located in front of a reference point of the vehicle, - a step of generating a representation (C) of the detected lane contour, - a step of travelling along part of the detected lane contour, via movement of the vehicle, - a step of projecting a vehicle (VEH) reference point (O) on the representation (C), - a step of plotting the travelled lane contour from the projected point (M').

Description

Method and on-board driving aid device with exceeded lane contour

[0001] [The present invention relates to a method and an on-board device for driving assistance with generation of the outline of an exceeded track.

[0002] The lane contours on the ground are traditionally detected by the vehicle's sensors to assist it in its driving, however these lane contours are not the subject of memorization for later use.

[0003] In document WO201468094 certain information from the past, such as the history of turns, is used for the generation of a horizon for an advanced driver assistance system.

[0004] In document US10160281, a driving history map is constructed from measurements of the roughness of the road along the journeys made, this characteristic representing the quality of the road then serving to anticipate the choice of the profile of the road. suspension to be applied to the suspension system.

[0005] These driving behavior or road quality histories do not

therefore do not make it possible to locate the vehicles behind in relation to the tracks and to anticipate their behavior, nor to offer the driver a

representation of the rear environment without the vehicle having any means of environmental perception, such as a camera, at the rear.

One of the aims of the invention is to remedy at least part of the

disadvantages of the prior art by providing an on-board method of driving assistance with tracing of the contour of the lane passed. This feature makes it possible to define the lanes delimited by the traces of the contour of the exceeded lane and to be able to associate detected objects with said lanes and to apply the rules of conduct to them and / or to display said lanes and said objects on said lanes. without having a rear camera. Indeed, two rear radars for example would provide information but this information would not be reliable enough to qualitatively represent the rear environment to the driver and constitute for him a decision aid, knowing that erroneous information is on the contrary a source of danger. . In addition, a radar can detect objects and lane edges, but not ground marking lines.

[0007] To this end, the invention provides an on-board method of assisting in driving a vehicle comprising:

- a step of detecting a lane contour located in front of a vehicle reference point,

- a step of generating a representation of said detected contour,

- a displacement definition step,

- a step of projecting the reference point of the vehicle on the representation,

a step of tracing said exceeded contour from the projected point;

which allows on the basis of available geometric information and

kinematics to be able to reconstruct, without additional sensors or connectivity with other vehicles, the outdated outline.

[0008] Thanks to the invention, also applicable for an autonomous vehicle, the detected lane contour makes it possible to constitute the route of the road markings exceeded without having a rear camera or any other rear sensor detecting lane contours.

[0009] According to particular embodiments: the track contour is a

road markings and / or a track edge.

[0010] According to an advantageous characteristic, said steps are carried out

at the same time for several lane contours, which makes the process adaptable to any type of traffic lane, even complex.

[0011] According to another advantageous characteristic, the representation of said contour is a spiral, or a polynomial of order 3, or a series of polynomials of order 3 or a spline of spirals.

[0012] According to another advantageous characteristic, the projection step comprises at least one iterative sub-step of searching for the point of projection of the reference point of the vehicle on the representation, in particular by using a Newton optimization method. -Raphson, which optimizes the projection time. [0013] According to another advantageous characteristic, the projection step comprises a sub-step of initializing the at least one iterative search sub-step from a first identified point of the representation of said contour.

[0014] Advantageously, the representation of said contour is a spiral of

length L, curvature of the origin cO and rate of change of curvature c1, and said first point is the midpoint of the spiral.

[0015] According to an advantageous characteristic, the projection is orthogonal, within a tolerance of approximately 5 °, which is easy to identify trigonometrically.

[0016] According to another advantageous characteristic, the plotting step comprises a sub-step for calculating intermediate points, the discretization step of which is a function of the speed of the vehicle, which allows an optimized plot without a point with low added value.

[0017] According to another advantageous characteristic, an output of the tracing step of said exceeded contour is a point cloud, which subsequently allows storage and simple memory management.

[0018] According to another advantageous characteristic, the step of generating a representation of said detected contour comprises a sub-step of recalculating the length of the representation of said contour.

The advantage of including a step of storing at least part of the trace of said exceeded contour allows display of the past of the journey.

According to an advantageous characteristic, the projection step comprises a sub-step of validation of said reference point of the vehicle projected on the representation, which makes it possible to robustify the projection.

[0021] According to another advantageous characteristic, the plotting step comprises a sub-step aimed at geometrically ordering said intermediate points, which makes it possible to keep in memory only the most relevant points.

[0022] According to another advantageous characteristic, the method comprises a sub-step aimed at evaluating an error associated with the projected point by calculation of the variance and error propagation, which makes it possible to robustify the method.

Advantageously, the reference point of the vehicle corresponds to the middle of the segment constituted by a rear axle of the vehicle, which allows better represent the vehicle, in particular when changing lanes, to avoid false lane change detections.

[0024] Advantageously, the method comprises a step of displaying on a screen the trace of said exceeded contour

[0025] According to another advantageous characteristic, the method comprises a step of associating an object with a path delimited at least partially by said trace of said exceeded contour, which makes it possible to display the situation of the objects detected at the rear. of the vehicle in relation to the plotted lanes displayed.

[0026] The invention also relates to an on-board driving assistance device comprising:

- a means of detecting a lane contour located in front of a reference point of the vehicle, in particular a sensor, and more particularly a front camera,

- means for generating a representation of said contour,

- a means of definition of displacement

- a means of projecting the reference point of the vehicle on the representation,

- A means for tracing said protruded contour from the projected point, this device has advantages similar to those of the method.

[0027] The invention also relates to a motor vehicle which includes such a device, said vehicle being in particular devoid of contour detection means located behind said reference point.

[0028] The invention also relates to a computer program comprising instructions for implementing the steps of such a method when said program is executed on a computer, the advantages being the same as those of the method.

[0029] The accompanying drawings illustrate the invention:

[0030] [Fig.1a] Figure 1a illustrates the principle of the invention at the time of

starting the vehicle and

[0031] [Fig.1b] Figure 1b illustrates the principle of the invention at the next instant taking place after a movement. [0032] [Fig.2] Figure 2 shows a functional flowchart of the method according to the invention.

[0033] [Fig.3] Figure 3 shows a block diagram of the method according to the invention.

[0034] [Fig.4] Figure 4 shows a flowchart of the projection step of the

method according to the invention.

[0035] [Fig.5] Figure 5 shows an illustration of the plotting step of the method according to the invention.

[0036] [Fig.6a] Figure 6a shows an illustration of a sub-step of the plotting step of the method according to the invention for a first use case.

[0037] [Fig.6b] Figure 6b shows an illustration of a substep of the plotting step of the method according to the invention for a second use case.

[0038] [Fig.7] Figure 7 shows a schematic view of a display using the method according to the invention.

[0039] [Fig.8] Figure 8 shows a schematic view of a use case of driving assistance using the method according to the invention.

Throughout the text, the directions and orientations are designated with reference to a direct orthonormal reference XYZ conventionally used in automotive design, in which X denotes the longitudinal direction of the vehicle, directed towards the front, Y is the transverse direction to the vehicle, directed to the left and Z is the vertical direction directed upwards. The angle Q being the vehicle's yaw angle, by convention positive when it turns to the left and negative when it turns to the right. The concepts "front" and "rear" are indicated with reference to the normal direction of travel towards the front of the vehicle. Throughout the description, the term “substantially” means that a slight deviation can be allowed with respect to a determined nominal position or orientation, for example “substantially perpendicular” means that a deviation of the order of 5 ° per in relation to a strictly perpendicular orientation is allowed within the framework of the invention. For clarity, identical or similar elements are marked with identical reference signs in all figures.

[0041] Vehicles equipped with driving assistance services, or even

autonomous vehicles, receive data from multiple sensors. The invention aims to optimize the use of data from vision sensors, ie sensors such as cameras, lidar or radar. More particularly, the invention, on the basis of the information on the contours of lanes obtained from these sensors, derives therefrom from the plots of the contours of exceeded lanes. The lane contours can be markings on the ground, in particular detected by cameras, or else lane edges detected by radars. With data from a single sensor or with perception algorithms, which can merge or combine data from different sensors, the vehicle obtains a

representation of the contours of the track stretching out in front of him. The invention aims to obtain from this information a representation of the lane contours, that is to say in particular the markings on the ground or the edges of the road, overtaken and left behind the ego vehicle in order to improve the assistance services. conduct.

Indeed, the information of the contours of the past lane will be used for driving assistance methods, in particular via the association of objects located at the rear of the vehicle ego with one lane, which makes it possible to apply to said objects rules of conduct and not only kinematic rules. These objects are for example detected by a side and / or rear radar and / or 360 ° lidar located on the roof of the vehicle. Thus, for functions such as collision warning or trajectory prediction, for example, a coherent association of the objects with the lanes will make it possible to predict their potential behavior (changing lanes, keeping in the lane, etc.) and then forecasting more efficiently. the trajectory and probable collisions of the ego vehicle with the various surrounding objects.

[0043] In addition, the past of the lane contours is also useful when the vehicle is backing up, especially if the vehicle does not have a rear camera to provide information on the lines located at the rear. Likewise, in the case of a vehicle equipped with such sensors, but when there is a momentary unavailability of the detection of lines by the sensors, the past of the lane contours may allow interpolation for a predetermined maximum distance.

[0044] Furthermore, to help the driver in his driving, the display on a man-machine interface of a representation of the past of the lane contours is of interest. Figure 1a illustrates the starting point, preferably identified by the time of starting the vehicle ego VEH, the moment from which the detection of the lane contour in front of the vehicle ego VEH begins. More precisely, it involves the detection of a lane contour situated in front of a reference point O of the vehicle ego to which the geometric coordinates (0,0) are assigned in the reference point of the vehicle ego VEH. The reference point O associated with the vehicle ego is preferably chosen as being the middle of the segment formed by the rear axle of the vehicle ego VEH and is represented in FIG. 1a by a non-solid cross. This reference point O thus chosen is more stable with respect to the calculations of rotations and vibrations of the vehicle and avoids, with respect to a reference point which would be chosen at the front of the vehicle, false detections linked to changing lanes in particular. .

[0046] The sensor, preferably a camera located at the front of the ego VEH vehicle and oriented towards the front, detects lane contours via the markings on the ground and in particular in this example the line located to the right of the ego VEH vehicle. Raw data from a sensor can be in the form of points or third degree polynomials and in the case of using multiple sensors their data is merged when they match the same item, the track contour data is then transformed to generate a spiral C describing the detected line shape. The spiral, also called the Cornu spiral or Euler’s spiral in English, is a curve of affine space of dimension two. It is known to use spirals in the road field since the geometric design of roads itself uses these plan profiles. Road layouts are therefore commonly designed and defined by spirals. Spirals allow you to represent straight lines, turns to the right, to the left and to make them follow each other easily.

A spiral is defined by three elements:

- the length L of the arc of the spiral,

- the curvature co at the origin of the spiral, and

- here the rate of variation of the spiral curvature,

the spiral curvature c (l) being proportional to its length I:

[0048] [Math. 1] c (Z) = c ₀ + q! V on [0, L]

The spiral C is described by:

[0050] [Math. 2]

C = (M ₀ , y ₀ , C _Q , c _lt L)

[0051] Where

- Mo is the point of origin of the spiral C with geometric coordinates in the vehicle frame of reference (xo, yo), and

- Yo is the angle of the tangent at the point of origin of the spiral.

[0052] Along the spiral the angle of orientation varies and at a length I it is equal to:

[Math. 3]

[0053] and the coordinates of a point (x (l), y (l)) belonging to the spiral are:

[0054] [Math. 4]

[0055] The point evaluation on the spiral (x (l), y (l)), which will take place in various steps of the process as we will see below, can advantageously use Fresnel integrals.

In Figure 1a, the spiral C shown of length L has the point

of origin Mo the projection of the reference point O on the spiral C, materialized in figure 1a by a cross full of coordinates (xo, yo).

FIG. 1b illustrates a time step after a first displacement of the vehicle ego VEH, after the plotting step (T). The ego vehicle (VEH) has therefore advanced along the initial spiral C, part of this initial spiral C has been passed, this part is represented by dotted lines between the point Mo of origin of the initial spiral C and the projection orthogonal of the reference point O of the vehicle ego on the initial spiral C. This projected point M ', represented by a solid cross in figure 1b, has for coordinates (x'o, y'o) and divides the spiral into a length The not yet exceeded by the point of reference O of the initial spiral C and an exceeded length L-L '

corresponding to the length of the segment [MoM '] corresponding to the protruded part of the initial spiral C. The updated spiral C' is therefore of length L 'not yet exceeded and the protruded part of the initial spiral C is represented by dotted lines. Here, a straight line path being shown, the yaw angle was not mentioned as it remained zero.

[0058] Figure 2 illustrates the steps of the method according to the invention. As mentioned above, the method begins with a step D of detecting the track contour (marking on the ground, such as a line, or track edge), the track contour detection data corresponding for example to raw data such as as third degree polynomials, segments and / or points associated with a marking on the ground and coming from a sensor, such as a camera. Once the vehicle is awake, this step D of detection by the sensors takes place continuously at an execution frequency specific to each sensor. Each polynomial associated with the contour of a track can be associated with fields of characteristics via a data structure which describes it by associating it for example with the quality of the signal received, the nature (continuous, discontinuous) of the marking on the ground detected if the track outline corresponds to a marking on the ground.

[0059] The following steps are preferably executed by a dedicated computer, for example the vehicle computer hosting the driving assistance methods. Step R of receiving raw track contour data from the sensors is performed with a determined time step, in particular greater than or equal to the response time of the slowest sensor, that is to say to the duration necessary for the slowest time sensor to realize and deliver the result of its detection, for example a few milliseconds. This reception step R preferably comprises a sub-step (not shown) of chronological ordering of the data received from the various sensors for each track contour and a sub-step of merging these data and associating an identifier with each contour detected. The format of the data output from this receiving step R remains the same as the input format for the raw data.

In the next step D of definition of displacement, it is determined whether the

movement of the ego VEH vehicle between data reception and the instant current is known, that is to say defined, it being understood that even if the displacement (according to the coordinates x, y, z)) is zero it nevertheless remains defined, and if this displacement is defined then the process is continued with these data, and if not, these data are deleted in step S of deleting said track contour data because they are not located.

[0061] Then, a step G of generating a representation of the input data, more particularly a step G of generating or updating a

representation of the detected ground marking, in particular by a transformation of the raw data received in the previous reception step R. Thus, each track contour detected, and preferably identified by its identifier, is therefore transmitted preferentially in the form of a polynomial and then transformed in step G into a geometric shape representing the marking on the ground detected, preferably in a spiral C or in a spline of spirals, or for example in a polynomial of order 3 or in a sequence of polynomials of order 3.

Thus, each track contour is represented by a single spiral. However, we can also model a track contour by a spiral spline, i.e. a curve that includes several spirals connected in series. This modeling approach allows a better representation for elongated track contours. For example, when the invention is applied to spiral splines, when identifying the spiral segment that has just been passed, an entire spiral may correspond to that segment. The invention is described below with reference to the case of a single spiral, which is more fundamental since a spiral spline is formed only by spiral spirals, and searching for the past from a spiral spline amounts to find the past tense of a track contour represented by a single spiral. The invention can also be applied to track contours modeled by polynomials by replacing the equations related specifically to the spiral model with the reciprocal equations for the polynomial model. Preferably, each spiral C associated with an identified track contour polynomial keeps the identifier of said detected contour as well as its characteristic fields.

This spiral generation step G also comprises, when it comes to updating a spiral C, a sub-step (not shown) of compensation for the displacement made by the vehicle ego VEH and determined at the displacement definition step D making it possible to update the spiral C. Thus the characteristics M ₀ (x ₀ , y ₀ ), ip ₀ , L of the spiral C are updated by taking into account the prediction of the displacement of the vehicle ego during the calculation step: from dx along the x axis, dy along the y axis and d0 for the yaw angle by application of the rules of trigonometry, xo becoming (xo-dx). cos (0) + (yo-dy). sin (0) and yo becoming - (xo-dx). sin (0) + (yo-dy). cos (0) and y ₀ becoming y ₀ - 0, c ₀ , c _t remaining unchanged, in addition it was chosen to keep the length L of the spiral unchanged at this substep.

[0063] Optionally, when the quality of the received signal is part of the

characteristics associated with the lane contour then an intermediate sub-step (not shown) of aggregation of the input data from the camera and / or other sensors and / or with the points in memory is added between the sub-step ( not shown) displacement compensation and projection step P, this aggregation sub-step provides for choosing the values having the lowest error rate and if necessary, for example in the event of momentary failure of the sensors or 'invalidity of the values received by the sensors (for example when entering a tunnel when the lights are not yet lit) to choose the spiral in memory by substituting it for the faulty or invalid data of the sensor (s).

Then is initiated the step P of projection of the reference point O of the ego vehicle on each representation of the lane contour generated in step G

previous, i.e. on the updated spiral C, this step being explained in the following figure. Preferably, the point projection can be slaved to the speed of the vehicle ego VEH so as to have less frequent sampling at high speed. Indeed, a projection every meter at 90 km / h is of no descriptive interest and will fill the memory unnecessarily. Not

sampling associated with the projection step P is therefore preferably a function of the speed so as not to calculate unnecessary points.

If the projection in step P could not be achieved (for example: the vehicle has not moved, the vehicle has advanced too far and the entire representation of the lane contour is exceeded without continuity with the present , change of trajectory related to an unknown track contour for the moment ...), then no addition cannot be added to this representation of the track contour, a new representation of the track contour, preferably with a new identifier, will be started at the next iteration. Once the projection has been carried out, that is to say the point M 'obtained, a step T of generating a plot of the representation of the track contour exceeded as a function of the stored points. Preferably, the plot is a cloud of points, comprising the stored projected points. After the first calculation step, including a movement of the ego VEH vehicle, we therefore have at least one projected point stored, that is to say that the outline of the track contour exceeded, that is to say from the past , is at least a cloud of two points, the first point being the point Mo of origin of the initial spiral C and the second point the point M 'projected onto the initial spiral C after movement of the vehicle ego and at the same time the spiral has been update.

A step M of storing and updating the memory then takes place either consecutively or in parallel with the tracing step T. Thus, this first new projected point is recorded in the memory of the computer that hosts the process, for example the ECU-ADAS (from English Electronic Control Unit - Advanced Driver Assistance System) driving assistance computer.

The steps of this method are executed in parallel in the case where

several lane contours, for example the right lane limit and the left lane limit of the ego VEH vehicle, are detected.

At each new loop at least one point is added to the plot thus

completed in step T and the memory in step M, knowing that the memory is for example limited to 50 projection points with FIFO (acronym for First in First Out) first-in-first-out logic.

[0069] The execution of the process is for example organized so that

each loop lasts a predetermined maximum duration, for example 40ms. and that the plot is generated or updated at 40ms. This execution step allows the process to be able to interact with other driving assistance processes and in particular to provide the layout of the lane contour representations to other driving assistance services.

FIG. 3 represents an overall flowchart of use of the method and more specifically of communication between the output data of the method. described above and another method of driving assistance, in particular of representation on a man-machine interface with association of the objects detected at the rear of the vehicle with the lanes traced in the tracing step T. In this example, with as input the step E-0 of data acquisition by at least one sensor, more particularly of a camera which films towards the front of the vehicle.

The data received is used in step D of detecting the track contour

(road markings, such as a line, or edge of the track). Steps D to M of the method as described above are carried out and symbolized by the dotted arrow between step D and step M for storing. At the same time, the data from the sensors (camera, radar, etc.) received in step E-0 may contain data associated with objects, and give rise to a step E-1 of object detection. The sensors used for object detection may not be the same as those used for lane contour detection and may even be located elsewhere on the ego vehicle. The fact of having generated in step T a plot of the exceeded ground markings makes it possible, in combination with the detection of objects, to proceed to a step E-2 of object-channel association for each object detected behind the point reference of the ego vehicle and belonging to one of the lanes delimited by the traced exceeded lane contour representations.

FIG. 4 represents a flowchart of step P of projecting the

method, in which it is considered that the detected track contour is represented by the spiral C generated in step G. This projection step P is relatively long and limited in time by a stopwatch which exits the step after a duration of 7 milliseconds for example.

The Newton-Raphson method chosen for the search for the point of

projection uses an iterative method made up of several nested loops. The initialization sub-step PJni of this method consists in defining a first point (soj, with i = 0) of initialization of the recurrence belonging to the spiral C from which we will initiate the search. Preferably, this first point is an identified point of the spiral C, calculated for example using the Fresnel integrals, corresponding to its midpoint in terms of length: , let so, i = L / 2 and to initiate the recurrence we set n = 1.

For reasons of better understanding of figure 4 the sub-step (PJni) is not shown in this preferred embodiment but so as to present a clearer sequence of iterations of i, with so, i, = iL / 2; i being between 0 and 2 and the first initialization value being i = 0.

Indeed, this projection step P comprises an iterative step of

search for the point of orthogonal projection of the reference point O associated with the ego vehicle VEH on the representation, here the spiral C.

The search for the projection point then consists, either of the real length I: I e R, the spiral C (l) e R ² , in searching for L * e R such that C (L *) or the orthogonal projection of the reference point O associated with the ego VEH vehicle on the representation, i.e. here on the spiral C.

For the search for the projection point we define the function f:

[0076] [Math. 5]

thread) = <0 - Cil), C il)>

[0077] Either:

[0078] [Math. 6]

And we find the zero of f by the Newton-Raphson optimization method. The principle of the Newton - Raphson method is based on the definition of a series of successive approximations of the equation f (x) = 0 starting from an initialization point of abscissa xo, estimated close to the solution, and from the latter we calculate a new point by plotting the tangent to the curve f in xo, this tangent intersects the abscissa axis in x1 which is calculated with the equation of the tangent y = f '(xn) (x - xn) + f (xn) This tangent intersects the x-axis when y = 0 so when f '(xn) (x - xn) + f (xn) = 0 which is also written f' (xn) ( x - xn) = -f (xn) x - xn = - f (xn) f '(xn) that is to say x = xn - f (xn) f' (xn) We therefore have the following recurrence relation: xn + 1 = xn - f (xn) f '(xn). So we get x1 and then we repeat these steps until the loop converges. For the loop to converge, the derivative of f must not cancel out.

Therefore we calculate the derivative of f:

[0081] [Math. 7] Which gives with the Math equations 1 to 4, with c (t) the curvature of the spiral at t as previously defined:

[0083] [Math. 8]

The search sub-step P_ff ’therefore corresponds to the bricks of the

iterative sequence of the Newton-Raphson method in which we calculate f and f, in which n is initially fixed at n = 1, and in which we begin by evaluating the spiral C at said first identified point initiating the search, namely the point of length s, which corresponds here to so, o at the first iteration, we then calculate the coordinates at the point s of the spiral: Mo, roj = (x (s), y (s)) and the angle at the point s of the spiral: ijJo, roj = y (e) and the rate of change of the curvature at the point s of the spiral: co, roj = ci (s); then we evaluate f (s), according to the Math 6 equation; and we evaluate the derivative of f: f (s), according to the Math equation. 8.

In the following output diagnostic sub-step P_S, the output condition of the double loop i, n is examined, namely whether

[0086] [Math. 9]

If 01 <^

With e equaling a predetermined threshold value close to zero, for example approximately 10 ⁷ . If the exit condition is satisfied then L * = s.

The chosen exit condition can be replaced by another, by

example:

[0089] [Math. 10]

| / (s) | <e

[0090] or even:

[0091] [Math. 11] And if the exit condition is not satisfied, we go to step P_ds in which we calculate a displacement ds on the curve of the spiral C according to the Newton-Raphson method:

[0093] [Math. 12]

ds = - / (s) // '(s)

Preferably in the following sub-step P_cons of consolidation on

first check that the new point corresponding to the length s + ds is on the spiral, that is to say that (x (s + ds), y (s + ds)) e C, which means for ds positive that ds becomes ds: = min (Ls, ds), and for ds negative that it becomes ds: = max (-s, ds). Another condition can be verified at this step, condition according to which if the absolute value of ds is less than a predetermined threshold, for example 1 cm, then one leaves the loop without taking into account this ds because it is judged of no interest, we therefore prefer to continue the search.

In the sub-step P_max of comparing the current value of n with a predetermined iteration threshold Nmax, for example equal to 10, or

preferably 5, if n is less than said iteration threshold Nmax then the process continues and if not, the loop is exited, this means that the

convergence will not be obtained and we start the substeps again with a new point (soj, with i = 2) of initialization which corresponds to (x (L), y (L)), i.e. l end of the spiral, so, 2 = L and so on and if this does not give a result, the third and last initialization point is the starting point of the spiral: (x (0), y ( 0)), or so, 3 = 0.

The choice of these three initialization points is in no way limiting, more or fewer points can be chosen, and different points can also be chosen, only one initialization point being necessary.

By continuing the method, that is to say when n <Nmax, the sub-step P_s + ds_cons of consolidation of said projection point s + ds obtained is executed. For that s + ds is calculated and becomes s and in order to decide if the solution s will be retained then we also check that this new s does not exceed the ends of the spiral [0; L] by forcing the new s to s = 0 if it had become negative and forcing it to L if it had become greater than L, and we increment n by 1.

Then in the P_C0 sub-step, the starting point of the spiral is updated, for this the spiral C is evaluated at the length s: C (s) according to the Math equation. 4, that is: (x (s), y (s), Y (e), c (s), ci) and if this point is different from the previous start of the spiral (x ₀ , y ₀ , (/ ₀ , c ₀ , <¾) it will replace it as a new start

spiral C.

In the next validation sub-step P_val it is checked whether the segment formed by the connection of the reference point O of the ego VEH and of the point M 'corresponding to the length s on the spiral forms a right angle with the spiral at this point. To do this,

- either the value of f (s) is calculated and if this value is sufficiently close to zero, for example less than a first predetermined validation threshold of 10 cm for example then the solution s is retained

- another alternative, which can also be combined with the comparison of f (s) with a first predetermined validation threshold, consists in calculating the cosine at the point of the solution s:

[0100] [Math. 13]

[0101] and if the latter is sufficiently close to zero, that is to say less than a second predetermined validation threshold, for example 0.05, then this solution s is retained as the projection: L * = s

and if not the solution s is rejected and we exit the loop by incrementing i to start a loop again with a new initialization point at the sub-step

P ini.

As illustrated by FIG. 5, the trace step T consumes the output of P_C0, that is to say that once the projection of the reference point O of the vehicle ego on the initial spiral C obtained, this last projected point M 'existing and belonging to the spiral, we define this projected point M' with coordinates (x'0, y'0) as being both the new point of origin of the spiral and the last point, historically, from the past part of the ground marking. In a preferred embodiment, the step T of tracing the contour exceeded beyond the point M projected M 'and of length dL = L- L', cf. Figure 1b, comprises a sub-step of calculation of intermediate points in which one carries out, as represented in FIG. 5 with a discretization step, dl, defined by the user, the calculation, using the Fresnel integrals for example, of the value of spiral C for a series of lengths, i.e. distances to the origin of spiral, dL- dl, dl_-2 * dl, ... dl_-k * dl until dl_-k * dl <0. Thus in Figure 5, the point (x (dL- 3dl), y (dL-3dl)), which falls outside the spiral: dl_-3 * dl <0, will not be kept in this series of intermediate points . Tracing this series of points reconstructs the contour of the passed track. This discretization step dl can be fixed at a predetermined value of 2 m for example, but it can also be a function of the speed of the vehicle ego so as to have less frequent sampling at high speed, with for example dl going up to 5 m above 90 km / h, as in the projection stage P.

Preferably, the tracing step T comprises a sub-step aimed at geometrically ordering the new set of projection points obtained, whether for the same track contour identifier or without having such an identifier, including the series of intermediate points, a geometric comparison is made for this to put them in decreasing order.

For example, as illustrated by Figure 6a, in the case where this new set of projection points already includes points from the past, ie behind (xo, yo), this means that in all these points an “old past” and a “new past”: one then compares its last point with the first point of G “old past” and more precisely their second coordinates, in a classical Cartesian coordinate system. For a better understanding, the points of G "old past" are represented connected to each other by a solid line and the points of the "new" past are represented connected to each other by a dotted line. For example, in Figure 6a when we compare the last point of the “new past”: (x (dL-2dl), y (dL-2dl)), with the first point of G “old past” we see that the old point (xo, yo), is well behind (x (dL-2dl), y (dL- 2dl)), the set of points of G “old past” is therefore retained as the historical continuation: the prolongation of “ new past ”. On the other hand, on the Figure 6b, we see that one of the old points: (xpi, ypi) is not behind (x (dL-2dl), y (dL-2dl)), this point of G “old past” is therefore eliminated, the others being kept. These cases can occur when backing up in a turn in particular.

[0104] Preferably, the plot has the form of a cloud of points.

Alternatively, another form of trace can be chosen, for example in the form of a line, by connecting the recorded points.

[0105] In addition, optionally as mentioned above, other

features that the only geometric coordinates are associated with each spiral identified and stored and can be used to give a different appearance to the plot depending on the features. For example, a memorized characteristic can be the nature of the marking on the ground (continuous or discontinuous for example) represented by the spiral at the projection point since this characteristic can be part of the characteristics detected by the sensors, and associated with the spiral. Thus, in the case where the plot is in the form of a line connecting points two by two, the nature of the line may depend on the characteristic of the nature of the marking on the ground assigned to each projection point. This example is not limiting. The plot can be virtual, in the sense that it is not displayed on a human machine interface (HMI) but serves as input data for driving assistance algorithms, but it can also be displayed on an HMI for the information of the driver, in particular when backing up and the vehicle does not have a rear camera and in this case it is preferentially chosen not to project again onto the past but to keep the track and the memory as what.

In the step M of storing and updating the memory which follows, or which takes place in parallel with the plotting step T, the new point s as well as the series of intermediate points are then stored knowing that 'a maximum number of memorized points is fixed for example at 50. In this, the

discretization according to the speed allows a better optimization of the memory.

[0107] The past points furthest from the position of the vehicle ego are

deleted when memory is full, which is done in a robust way thanks to the preparation already carried out in the sub-step, of the plotting step T, aimed at geometrically ordering said projection points.

[0108] Once these steps have been completed, the process is looped back to step G of

generation or updating of the spiral in which the spiral C is updated. Indeed, once the projection of the reference point O of the vehicle ego on the initial spiral C obtained, this last projected point M 'existing and belonging to with the spiral, one defined in the sub-step P_C0 this projected point M 'of coordinates (x'o, y'o) as being both the new point of origin of the spiral and the last point, historically, of the past part of the floor marking. The new length L ′ is then preferably calculated in step G of updating the spiral, as indicated in the description of FIG. 1b. This sub-step of calculating the new length L ′ could also be carried out at the end of the projection step (P) for example.

[0109] In addition, a sub-step, not shown in the figures, aimed at evaluating the error associated with the new point of origin of the spiral, which corresponds to the projected point M ′, can also be carried out. This sub-step can of course be carried out in another step once the projected point M ’has been obtained. The evaluation of the error corresponds to the calculation of the variance å (l), of the new point of origin of the updated spiral C. This step involves the error propagation of the previous initial point whose variance is å (0), which gives:

[0110] [Math. 14] å (l) =] å ^T

[0111] where J is the Jacobian of the function fi (xo, yo, ijJo, co, ci) = (x (l), y (l), ijj (l), c (l)), where x (l ), y (l), ijj (l), c (l) are given by Math equations 1 to 4. Thus, according to the example of Figure 1b x'o = x (l) and y'o = y (l). This variance å (l) is recorded as an accessory characteristic to the updated spiral C knowing that from this variance at the origin point of the spiral we can calculate the variance along the spiral. The updated spiral C is then stored geometrically with its associated characteristics.

[0112] The memory is emptied when the vehicle falls asleep. [0113] The method is advantageously used in driving assistance applications.

FIG. 7 illustrates a use in which the display of the trace of the past is offered to the driver. The driver of the ego VEH vehicle has at his disposal displayed on the HMI screen the vehicles behind him, each one assigned to a lane which has been previously identified during the execution of the process. For example, in this figure three objects have been detected behind the vehicle ego VEH, by means of a radar for example, they are vehicles VEH1, VEH2 and VEH3. Information such as the position and / or the relative distance of each object of the vehicle ego, its type, kinematic data such as speed and acceleration, the presence of the indicator (here represented by a gray area in the figure), etc. are part of the characteristics detected and associated with each object.

[0115] The process made it possible to trace the past of four markings on the ground,

delimiting three lanes: the lane of the ego VEH vehicle and an adjacent lane on each side. For this display use intended for the driver, an association step followed by a step of displaying on a screen the tracing of said exceeded contour, are added to the method, they use the stored data which are already ordered and these steps can be executed during the process (for example at the end of the storage step M) or outside the process by just calling the stored data.

In the additional association step, a detected channel is associated with each object if it exists. For example, for each object belonging to the zone delimited by the outer contour of the lanes delimited by the route of their marking on the exceeded ground, a step takes place of associating the object in question with a lane of said lanes. At the end of this association step, the objects were then associated with the lane in which they were detected, thus the first object VEH1 is associated with the adjacent lane on the right with respect to the lane in which the ego vehicle is traveling. , the second object VEH2 is associated with the same lane as the ego VEH vehicle and the third object VEH3 is associated with the adjacent left lane with respect to the lane in which the ego VEH vehicle is traveling. These associations are based on the position and / or relative distance information acquired by the sensor. Then the display step consumes the output of the association step as well as the data stored in step M of the method, this display on IΊHM will be used by the driver of the vehicle ego VEH in order to adapt his trajectory (ie keeping in the lane, changing lanes ...) and its speed according to the

dynamic behavior of other objects, even if it does not have a reversing camera. Indeed, it is necessary to know in which lane the other vehicles are in order to better anticipate their behavior as a function not only of kinematic but also semantic information, such as the rules of conduct, and to make decisions. Thus, in Figure 7 the ego VEH vehicle knows for example that it must adapt its speed so that the VEH1 vehicle located in its blind spot on the adjacent lane to its right can insert behind it.

FIG. 8 illustrates a use in which an improvement is proposed in the on-board function acting automatically and allowing a vehicle to follow another at an appropriate distance (ACC for Adaptive Cruise Control in English). In this embodiment, an association step is added to the method in which a detected path is associated with each object if it exists, as explained in the previous paragraphs. This step

association, especially when it is performed for the sole need of ACC, that is to say without HMI display, can for example be executed in parallel in the ACC computer which then calls the stored process data.

In fact, in the ACC function, the lateral and longitudinal control needs to know not only the C_ACC target to be followed but also information on the objects VEH1, VEH2, VEH3 surrounding the vehicle ego VEH, allocated on the critical channels that are in particular the path of the ego vehicle and the two adjacent paths. Information such as the position of each object, its type, kinematic data, the presence of the indicator (here represented by a gray area in the figure), etc., will be used by the function to adapt the trajectory and speed of the vehicle ego VEH according to the dynamic behaviors of these objects. In addition, depending on the context, the ACC function can change the target to follow if it considers that the level of risk associated with the first target exceeds a risk threshold for the ego VEH vehicle, for example if the target C_ACC is traveling slowly compared to the vehicle. VEH2 vehicle following in the ego vehicle lane. It is therefore useful to know in which lane the other vehicles are in order to better anticipate their behavior as a function not only of kinematic information but also of semantics (in relation to FIG. 8 to VEH2 AND C_ACC in particular).

[0120] These examples of application of the method according to the invention are illustrative and are in no way limiting.

[0121] This method can be applied to the automobile to use and / or visualize outdated markings on the ground, but can for example also be applied to the field of robotics.

Claims

[Claim 1] [Embedded method for assisting in driving a vehicle (VEH) comprising:

- a step (D) of detecting a lane contour located in front of a vehicle reference point (VEH),

- a step (G) of generating a representation (C) of said detected contour,

- a step (D) of definition of displacement,

- a step (P) of projecting the reference point (O) of the vehicle onto the representation (C),

- a step (T) of tracing said exceeded contour from the projected point (M ’).

[Claim 2] A method according to the preceding claim in which the representation (C) of said contour is a spiral (C), or a polynomial of order 3, or a sequence of polynomials of order 3 or a spline of spirals.

[Claim 3] Method according to any one of the preceding claims, in which the projection step (P) comprises at least one sub-step (P_ff, P_S, P_ds, P_ds_cons, P_s + ds_cons) iterative search for the projection point the reference point (O) of the vehicle (VEH) on the representation (C), in particular by using a Newton-Raphson optimization method.

[Claim 4] Method according to the preceding claim in which the projection step (P) comprises a sub-step (PJni) for initializing the at least one sub-step (P_ff, P_S, P_ds, P_ds_cons, P_s + ds_cons ) iterative search from a first identified point (so, i) of the representation (C) of said contour.

[Claim 5] A method according to any preceding claim in which the projection is orthogonal.

[Claim 6] A method according to any one of the preceding claims in which the plotting step (T) comprises a sub-step of calculating intermediate points, the discretization step of which is a function of the speed of the vehicle (VEH).

[Claim 7] Method according to any one of the preceding claims comprising a step (M) of memorizing at least part of the trace of said exceeded contour.

[Claim 8] A method according to any preceding claim in which the vehicle reference point (O) (VEH) corresponds to the middle of the segment consisting of a rear axle of the vehicle (VEH).

[Claim 9] A method according to any one of the preceding claims comprising a step of displaying on a screen the trace of said exceeded contour.

[Claim 10] On-board driving assistance device comprising:

- means for detecting a lane contour located in front of a vehicle reference point (O) (VEH), in particular a sensor, and more particularly a front camera,

- means for generating a representation (C) of said contour,

- a means of definition of displacement

characterized in that it also comprises:

- a means of projecting the reference point (O) of the vehicle (VEH) on the representation (C),

- a means of tracing said exceeded contour from the projected point (M ’).

[Claim 11] Motor vehicle (VEH) characterized in that it

comprises a device according to the preceding claim, said vehicle (VEH) being in particular devoid of contour detection means located behind said reference point (O).

[Claim 12] A computer program comprising instructions for carrying out the steps of the method according to any one of claims 1 to 9, when said program is executed on a computer.