EP3784987A1

EP3784987A1 - Method for a motor vehicle to select a preferred traffic lane to cross a toll area

Info

Publication number: EP3784987A1
Application number: EP19723324.0A
Authority: EP
Inventors: Jorge Da Silva; Guillermo PITA-GIL; Chrysanthi PAPAMICHAIL
Original assignee: Renault SAS; Nissan Motor Co Ltd
Current assignee: Ampere SAS; Nissan Motor Co Ltd
Priority date: 2018-04-23
Filing date: 2019-04-23
Publication date: 2021-03-03
Also published as: FR3080346B1; US11400935B2; KR20210003119A; JP2021522479A; FR3080346A1; US20210122374A1; CN112020631A; WO2019206860A1

Abstract

The invention relates to a method for a motor vehicle (100) to select a preferred traffic lane (230) to access a toll area (200) comprising a plurality of traffic lanes (210, 220), comprising steps: a) of detecting traffic lanes of the toll area, b) of determining, for at least some of said traffic lanes, a first item of data (d_ij) relating to the distance between the motor vehicle and the corresponding traffic lane, and a second item of data relating to the number of other vehicles situated on the corresponding traffic lane, c) of minimizing a cost function that depends on each first item of data and on each second item of data, so as to identify the preferred traffic lane, and d) of determining the possibility or the risk for the motor vehicle of changing traffic lane in order to move towards the preferred traffic lane.

Description

METHOD FOR SELECTING A MOTOR VEHICLE FROM A PREFERRED CIRCULATION PATHWAY THROUGH A TIRE AREA

TECHNICAL FIELD TO WHICH THE INVENTION REFERS

The present invention relates generally to the field of driving aids and autonomous vehicles.

It relates more particularly to a method for selecting by a motor vehicle of a preferred lane to approach a toll area comprising several lanes.

It also relates to a method for controlling an autonomous motor vehicle towards this preferred traffic lane.

BACKGROUND

Document DE102012022629 discloses a method of decision support for deciding on a lane to be used when a vehicle arrives on a toll area.

In this document, the vehicle is equipped with wireless communication means adapted to receive data transmitted by the toll area. These data relate to the open and closed traffic lanes, the means of payment accepted on each lane of traffic, and the number of third-party vehicles waiting on each lane of traffic (the latter information being available if the third-party vehicles are themselves equipped with means of communication).

The major disadvantage of this method is that it requires the establishment of a wireless communication between the motor vehicle and the toll area, which is in practice never guaranteed. It also requires equipping motor vehicles and toll areas with expensive means of communication.

OBJECT OF THE INVENTION

In order to overcome the aforementioned drawback of the state of the art, the present invention proposes a method in which the vehicle determines in a very reliable and secure manner which traffic lane it should preferentially use to cross the toll area, without have to establish communication with this toll area. More particularly, it is proposed according to the invention a method of selection by a motor vehicle of a preferred lane to access a toll area, comprising steps:

a) detection of taxiways in the toll area,

b) determining, for at least a portion of said traffic lanes, a first datum relating to the distance separating the motor vehicle from the corresponding driving lane, and a second datum relating to the number of third-party vehicles located on the road; corresponding traffic lane,

c) calculating the value of a cost function for each of the traffic lanes of said part, according to the first datum and the second datum corresponding to the traffic lane concerned, and to identifying the lane preferred circulation as the one for which the value of the cost function is the smallest of the calculated values, and

(d) determining the possibility or risk for the motor vehicle to change lanes of traffic to the preferred lane.

Thus, thanks to the invention, the choice of the traffic lane to be used to approach the toll area depends not only on the number of vehicles on each lane, but also on the distance separating the vehicle from each lane. and the potential danger of reaching the preferred lane. It thus allows a secure driving of the motor vehicle.

Preferably, this method uses only the equipment of the motor vehicle. It is therefore reliable that the toll area is or not equipped with communication means.

Other advantageous and non-limiting characteristics of the process according to the invention are the following:

- The motor vehicle is equipped with at least one telemetry sensor, in step b), the second data is an estimate of the number of third vehicles located on each of said traffic lanes, determined according to the measurements made by said sensor telemetry;

in step c), the value of the cost function is calculated for each of the circulation lanes of said part, as a function of the sum of the first corresponding data, weighted by a first coefficient, and the second corresponding data, weighted by a second coefficient;

- given a taxiway that is close to the taxiway used by the motor vehicle and which is located on the side of the preferred taxiway in relation to the taxiway used by the motor vehicle, in step d ), it is checked that the maneuvering time necessary for the motor vehicle to make a change of lane in order to reach a desired location of the said adjacent traffic lane is strictly less than the arrival time required for third-party vehicles traveling on the said lane. next traffic lane arrive at the desired location;

in step d), a dual criterion relating to the relative speed of the motor vehicle is checked with respect to the two third-party vehicles which roll in front of and behind the motor vehicle, on the neighboring roadway;

alternatively or additionally, in step d), a criterion relating to the maneuvering time necessary for the motor vehicle to change lanes is checked, the motor vehicle being equipped with a means for acquiring images and of a calculation unit, in step a), the image acquiring means acquires an image of the toll area and the computing unit processes said image to detect the open lanes of the toll area. and, in step b), the computing unit determines the first data and the second data for each open lane;

the motor vehicle being equipped with an image acquisition means and a computing unit, in step a), the image acquiring means acquires an image of the toll area, and in step b), the computing unit processes said image to evaluate the first data;

- the motor vehicle is equipped with a geolocation means, a memory storing a route map and a calculation unit, in step b), the calculation unit calculates the first data according to the geolocated position of the motor vehicle obtained by the geolocation means and the geometry of the toll area stored in the memory.

The invention also relates to a method for controlling an autonomous motor vehicle, comprising:

steps a) to d) of the selection process defined above, then

- A driving step of the motor vehicle considered towards the desired driving lane. Preferably, if the desired traffic lane is not close to the traffic lane used by the motor vehicle, it is expected, after the vehicle has changed a first lane, repeating said steps a) to d ).

DETAILED DESCRIPTION OF AN EXEMPLARY EMBODIMENT

The following description with reference to the accompanying drawings, given as non-limiting examples, will make it clear what the invention consists of and how it can be achieved.

In the accompanying drawings:

- Figure 1 is a schematic view of a motor vehicle adapted to implement a selection method according to the invention;

FIG. 2 represents in the form of a logic diagram an exemplary selection method according to the invention;

- Figures 3 to 6 are schematic top views of toll areas, on which different vehicles are shown, including the motor vehicle of Figure 1.

In preliminary, it will be noted that identical or similar elements appearing in the different figures will, as far as possible, be referenced by the same reference signs and will not be described each time.

In Figure 1, there is shown a motor vehicle 100 seen from above.

As shown in this figure, the motor vehicle 100 is here a conventional car, comprising a frame which is supported by wheels and which itself supports various equipment including a powertrain, braking means, and a steering unit. .

It may be a vehicle with manual steering, in which case it will be equipped with information display means for the driver, or, preferably, a self-driving vehicle. This is also the case of an autonomous vehicle that will be considered here in the rest of this presentation.

This motor vehicle 100 is equipped with sensors allowing it to locate in its environment so as to be able to drive independently, that is to say without human intervention.

Any type of sensor could be used. In the example shown in Figure 1, the motor vehicle 100 is equipped with a camera 130 facing the front of the vehicle to capture images of the environment at the front of the vehicle.

The motor vehicle 100 is further equipped with at least one telemetry sensor (RADAR, LIDAR or SONAR). It is more precisely here equipped with five RADAR sensors 121, 122, 123, 124, 125 located at the four corners of the vehicle and in the front center position of the vehicle.

The motor vehicle 100 is also equipped with a geolocation system 141, comprising for example a GNSS receiver (typically a GPS sensor).

In order to process the information provided by these various components and to be able to develop a driving instruction of the powertrain, braking means, and the steering unit, the motor vehicle 100 is equipped with a calculator 140.

This computer 140 includes a processor (CPU), a random access memory (RAM), a read-only memory (ROM) of the analog-digital converters, and various input and / or output interfaces.

Thanks to its input interfaces, the computer 140 is adapted to receive input signals from the different sensors.

The computer 140 is also connected to a memory 142 which stores a route map. We will consider here that it is a detailed cartography, in which the geometries of the toll areas are indicated.

The read-only memory of the computer 140 stores a computer application, consisting of computer programs comprising instructions whose execution by the processor allows the implementation by the computer of the method described below.

Finally, thanks to its output interfaces, the controller is adapted to transmit instructions to the various organs of the vehicle.

Figures 3 and 4 on the one hand, and 5 and 6 on the other hand, there are shown two toll areas 200 views from above.

These toll areas 200 each include a toll barrier 201 at which the user of each vehicle must pay a tax of passage. Each toll zone 200 also includes, to access this toll barrier 201, a number N of traffic lanes 210, 220, 230, 240 (with N equal to 4 in Figures 3 and 4, and N equal to 8 in Figures 5 and 6).

The toll gate 201 comprises, above each traffic lane, an LED panel on which a logo is represented. This logo can for example represent a red cross if the lane is closed to traffic, or a green arrow if the lane is open. It could also represent other reasons (a credit card if payment by credit card is possible, an orange "t" if remote payment is possible ...).

In the rest of this presentation, among the traffic lanes, we will distinguish:

the current circulation lane 210 being the traffic lane used by the motor vehicle 100 under consideration,

the neighboring traffic lanes 220 being the two traffic lanes located on either side of the current lane 210, and

- The preferred taxiway 230 as the taxiway which, as will become clear later in this presentation, is the one deemed most appropriate to allow a quick and safe passage of the toll barrier 201.

Taxiways marked "240" will be those that do not meet any of the three criteria listed above.

As shown in Figures 3 to 6, it will be considered here that motor vehicles other than the aforesaid motor vehicle 100, hereinafter called third vehicles 300, 310, 320, also roll on the taxiways of the toll area.

Among these third-party vehicles, we will distinguish:

the preceding vehicle 310 as being the third vehicle which rolls on one of the two adjacent traffic lanes 220, namely that on which the motor vehicle 100 wishes to disengage, and which is at the front of the motor vehicle 100, and

the next vehicle 320 being the third vehicle traveling on the same neighboring road 220, which is at the rear of the motor vehicle 100.

When the motor vehicle 100, which is considered to be autonomous here, approaches a toll area 200, it must choose one of the circulation 210, 220, 230, 240. Otherwise formulated, the computer 140 must judge the opportunity to change lanes of traffic on arrival in a toll area, in order to pass as quickly and safely the barrier of toll 201.

For this, its computer 140 implements a method comprising several main steps.

A first preliminary step is for the computer 140, to verify that the data measured by the various equipment of the motor vehicle 100 (RADAR sensors and cameras) are exploitable.

It can indeed happen, especially depending on the weather, that this is not the case.

For this, the computer 140 receives from each of these devices a confidence index (expressed here as a percentage of confidence in the reliability of the measurement it performs), which it compares to a predetermined threshold .

If the confidence index is not high enough, the process stops. In the opposite case, the method illustrated in FIG. 2 is implemented.

The first step a) of this process is to determine the geography of the places.

For this, the computer 140 uses either the camera 130 alone, or the geolocation means 141 coupled to the memory 142, or all of these elements in combination.

More precisely here, it acquires an image captured by the camera 130, and the geolocated position of the motor vehicle 100.

Given this geolocated position, the motor vehicle 100 can find in the memory 142 a plan of the toll area 200.

He can thus determine the number N of lanes of the highway area 200.

The computer 140 then assigns to each lane an identifier hereinafter denoted "j". This identifier is here a natural integer between 1 and N, the traffic lane identified by the integer j = 1 being the leftmost lane.

Then, by an image processing process acquired, the computer 140 locates the logos located above each of the traffic lanes. It then identifies the shape and color of each logo and thus determines what are open traffic lanes.

In the configuration illustrated in FIG. 3, the traffic lane identified by the integer j = 4 is closed while the other lanes are open.

In the configuration illustrated in Figure 4, all traffic lanes are open.

In the configuration illustrated in FIGS. 5 and 6, the traffic lanes identified by the integers j = 4, j = 6 and j = 8 are closed while the other traffic lanes are open.

During a second step b1), the computer determines how far the motor vehicle 100 is away from each open lane.

It calculates for this purpose, for each open lane, a first data relating to the distance separating the motor vehicle 100 from this lane.

This first datum is here an estimate of the Euclidean distance d separating the motor vehicle 100 and the point situated at the center of the traffic lane considered, at the level of the toll barrier 201.

The index "i" here corresponds to the natural number identifying the current running lane 210, and the index "j" corresponds to the natural number identifying the traffic lane 210, 220, 230, 240 considered.

This Euclidean distance dy is obtained taking into account the location of the motor vehicle 100 and the plan of the toll area 200 read in the memory 142.

During a third step b2), the computer 140 evaluates the size of each open lane of the toll area 200.

For this, the computer 140 calculates, for each open lane, a second data relating to the number of third vehicles 300, 310, 320 located on this lane.

This second data is here an evaluation of the number n _j of third vehicles 300, 310, 320 located on this lane.

This evaluation is obtained here thanks to the measurements made by the RADAR sensor 122 located in the front center position of the motor vehicle 100, by the RADAR sensor 121 located in the front left position of the motor vehicle 100 and by the RADAR sensor 123 located in the front right position of the motor vehicle 100. It is refined by a processing of the image acquired by the camera 130 of the motor vehicle 100.

The fourth step c) consists in selecting, among all the traffic lanes to which the motor vehicle 100 can easily access, the one where the waiting to pass the toll barrier 201 will be the shortest.

The criterion which is used for this purpose is a cost function J, which is a function of at least the estimate of the Euclidean distance separating the motor vehicle 100 from each lane, and the evaluation of the number n _j of vehicles. on each lane.

This Jy cost function could be expressed in a variety of ways. It is expressed here as follows:

Jy = dy ^ i _j + n _j -Y _j

where z, _] and Y _j are two weighting factors.

The values of these weighting factors are chosen so as to favor either the speed of passage of the toll barrier (even if the motor vehicle 100 has a large number of lane changes to operate), or the comfort of the passengers in question. selecting a traffic lane preferably close to the current lane 210. The values of these weighting factors can be either predetermined (stored in the read-only memory of the computer) or can be parameterized according to the preferences of the passengers of the vehicle or the vehicle. category of the vehicle (ambulance, goods transport vehicle ...). These weighting factors can also be expressed in the form of functions, for example in the form of functions of the data dy, n, to which they relate (affine function, inverse function, square function, etc.).

Be that as it may, the calculator uses the same mathematical formula to calculate a value of the cost function Jy for each of the taxiways of the toll area 200.

The preferred taxiway 230 is then that for which the cost function Jy is minimum. Examples illustrating, in different configurations, which traffic lane is preferred will be detailed later in this discussion. The fifth step d) is to determine whether it is possible for the motor vehicle 100 to change lanes 210, 220, 230, 240 without risk in order to move towards the preferred lane 230.

This step can be implemented in various ways.

Here, the computer 140 calculates the operating time ÎºGO which will be necessary for the motor vehicle 100 to reach the nearby traffic lane 220 (on which it wishes to disengage) and where 221 this vehicle will end after this change of lane.

Then, if one is in the presence of a previous vehicle 310 and / or following 320, the computer 140 calculates the arrival times ÎOBJ that will be necessary for these vehicles 310, 320 reach the location 221.

The criterion for determining whether it is possible for the motor vehicle 100 to change lanes of traffic then simply consists in verifying the following inequality:

Î _EGO <min (to _Bj ) + ôt

where is a predetermined safety margin and stored in the read-only memory of the computer 140.

If this inequality is not verified (which means that there would be a risk to change lanes), the motor vehicle 100 remains on its lane 210 and the method is reset in step a).

In the opposite case, the computer 140 implements a step e) of controlling the steering unit of the motor vehicle 100 so that the motor vehicle 100 passes from the current circulation lane 210 to the neighboring lane 220 (the one located on the side of the desired taxiway 230).

At this stage, one can first consider the case where the adjacent traffic lane 220 and the desired circulation lane 230 are combined (case of Figure 3). In this case, the process ends here.

In the opposite case (case of Figure 4), it is not expected that the motor vehicle 100 directly rejoins the desired traffic lane 230 by changing lane again without prior control.

On the contrary, it is intended to reset the entire process before changing again the motor vehicle 100 taxiway. Thus, if the configuration has changed, the motor vehicle 100 can adapt quickly to this change.

The three examples shown in FIGS. 3 to 6 can now be described in greater detail.

In the first example shown in Figure 3, the motor vehicle 100 rolls on the current running lane 210 identified by the integer i = j = 2.

The taxiway 240 identified by the integer j = 4 is closed.

The calculator 140 then calculates 3 cost functions J21, J22 and J23.

The desired taxiway 230 will then be the one where the cost function is the lowest. It is understood that the result will strongly depend on the weighting factors used.

Thus, if conservative behavior is preferred, the motor vehicle 100 will choose, given the small number of vehicles on its lane 210, not to change lanes.

On the contrary, if a more reactive behavior is preferred, the motor vehicle 100 will choose, given the very low number of vehicles on the nearby traffic lane 220 on the left, to change lanes.

In this case, the motor vehicle will first check that it can change lanes safely. Here, the preceding vehicle 310 and the next vehicle (not visible) being far from the place 221 that the vehicle wishes to reach, the motor vehicle 100 can safely disembark in the desired traffic lane 230.

In the second example shown in Figure 4, the motor vehicle 100 rolls on the current running lane 210 identified by the integer i = j = 2.

All the traffic lanes of the toll area 200 are here open. Three third-party vehicles 300, 310, 320 are here located on each taxiway, with the exception of the right lane where only one third-party vehicle 300 is located.

The calculator 140 then calculates four cost functions J21, J22, J23 and J24.

The chosen taxiway will be the one where the cost function is the lowest. The result will then again strongly depend on the weighting factors used. Thus, the motor vehicle 100 will choose to join the traffic lane 220 on the right only if a very reactive behavior is preferred. In this case, the motor vehicle 100 will again check that it can change lanes safely. In the present case, the preceding vehicle 310 and the following vehicle 320 being far from the place 221 of the adjacent traffic lane 220 that the vehicle wishes to reach, the motor vehicle 100 can safely displace in this nearby traffic lane 220. He can then again calculate the cost function for the four lanes before choosing whether he stays on his lane or if he actually joins the traffic lane originally desired.

In the third example shown in FIGS. 5 and 6 (at two successive instants), the motor vehicle 100 initially rolls on the current running lane 210 identified by the integer i = j = 4.

This lane, as well as those identified by the integers j = 6 and j = 8 are closed. The vehicle must therefore change lanes.

The calculator 140 then calculates five cost function values J _4i , J ₄ 2, J43, J45 and J47.

The chosen taxiway will again be the one where the value of the cost function is the lowest. The result of this choice will again strongly depend on the weighting factors used, but in all cases, the motor vehicle 100 will choose to change lanes.

As shown in Figure 5, he may choose to go to the desired traffic lane 230 located furthest left.

However, as shown in Figure 6, after changing a first time lane, he can see that it is not possible for him to change lane again since the place 221 where he wishes to dislocate is already occupied by a previous third vehicle 310. In this event, the computer makes the decision not to change lanes to pass the toll gate 210.

Different variants of the embodiment described here are conceivable.

In particular, step d) could be implemented differently.

As a first example, it would be possible, to verify the safe nature of dislocation, to consider more vehicles. It would thus be possible to calculate PEO times not only for vehicles preceding 310 and following 320, but also the PEO times of any other third vehicle 300 being able to reach the place 221 towards which the motor vehicle 100 wants to go (including those third vehicles having put their turn signals to dislodge to the track neighboring traffic).

As a second example, it would be possible as an alternative, to verify the safe nature of a dislocation, not to compare times EGGO, PEI, but to control relative velocity criteria of the vehicles relative to each other.

This control could thus be based on a comparison of the relative speed of the motor vehicle 100 with respect to the preceding vehicle 310 with a first threshold, and on a comparison of the relative speed of the motor vehicle 100 with respect to the following vehicle 320 with a second threshold, to verify that these relative speeds are compatible with a safe lane change.

In the embodiment described with reference to the figures, the vehicle was autonomous. Alternatively, one could predict that it is not. In this case, the fifth step e) will no longer be to automatically drive the motor vehicle 100 to the desired driving lane 230, but rather to display on a screen of the vehicle information allowing the driver to know which way it should head for the toll gate as quickly and safely as possible.

Claims

A method of selecting by a motor vehicle (100) a preferred traffic lane (230) for accessing a toll area (200) comprising a plurality of traffic lanes (210, 220, 230, 240), including steps :

a) detection of taxiways (210, 220, 230, 240) of the toll area (200),

b) determining, for at least a portion of said traffic lanes (210, 220, 230, 240), a first datum (d) relating to the distance separating the motor vehicle (100) from the traffic lane (210). , 220, 230, 240), and a second datum (n _j ) relating to the number of third vehicles (300, 310, 320) located on the corresponding taxiway (210, 220, 230, 240),

c) calculating the value of a cost function (Jy) for each of the traffic lanes (210, 220, 230, 240) of said part, as a function of the first data (dy) and the second data ( n,), and identifying the preferred traffic lane (230) as the one for which the value of the cost function (Jy) is the smallest, and

d) determining the possibility or risk for the motor vehicle (100) to change lanes (210, 220, 230, 240) to the preferred traffic lane (230).

2. A selection method according to the preceding claim, wherein, the motor vehicle (100) being equipped with at least one telemetry sensor (121, 122, 123, 124, 125), in step b), the second datum (n,) is an estimate of the number of third vehicles (300) located on each of said traffic lanes (210, 220, 230, 240), which is determined based on measurements made by said telemetry sensor (121, 122). , 123, 124, 125).

3. Selection method according to one of the preceding claims, wherein, in step c), the value of the cost function (Jy) is calculated for each of the traffic lanes (210, 220, 230, 240). of said part, as a function of the sum of the corresponding first data item (dy), weighted by a first coefficient (z ,,), and the corresponding second data item (n), weighted by a second coefficient (g,).

4. Selection method according to one of the preceding claims, in which, given a taxiway (220) which is adjacent to the taxiway (210) taken by the motor vehicle (100) and which is located on the side of the preferred taxiway (230) with respect to the traffic lane (210) taken by the motor vehicle (100), in step d), it is checked that the maneuvering time (Î _EGO ) necessary for the motor vehicle (100) to make a change of lane in order to achieve at a desired location (221) of said adjacent traffic lane (220) is strictly less than the arrival time (toBj) necessary for the third vehicles (310, 320) traveling on said neighboring traffic lane (220) to arrive at the desired place.

5. A selection method according to one of the preceding claims, wherein, given a traffic lane (220) which is adjacent to the lane (210) taken by the motor vehicle (100) and which is located on the side of the preferred driving lane (230) relative to the lane (210) used by the motor vehicle (100), in step d), a dual criterion relating to the relative speed of the motor vehicle (100 ) with respect to the two third vehicles (310, 320) which roll in front of and behind the motor vehicle (100), on said adjacent traffic lane (220).

6. A selection method according to one of the preceding claims, wherein, the motor vehicle (100) being equipped with an image acquisition means (130) and a computing unit (140), at step a), the image acquisition means (130) acquires an image of the toll area (200) and the computing unit processes said image to detect the open traffic lanes of the parking area. toll, and, in step b), the computing unit (140) determines the first data (d) and the second data (n,) for each open lane.

7. A selection method according to one of the preceding claims, wherein, the motor vehicle (100) being equipped with an image acquisition means (130) and a computing unit (140), at step a), the image acquisition means (130) acquires an image of the toll area (200), and in step b) the computing unit (140) processes said image to to evaluate the first data (dy).

8. A selection method according to one of the preceding claims, wherein, the motor vehicle (100) being equipped with a geolocation means (141), a memory (142) storing a route map and a calculation unit (140), in step b), the computing unit calculates the first datum (dy) as a function of the geolocated position of the motor vehicle (100) obtained by the geolocation means (141) and the geometry of the toll area (200) stored in the memory (142).

9. A method for controlling an autonomous motor vehicle, comprising:

steps a) to d) of the selection method defined in one of the preceding claims, and then

- A driving step of the motor vehicle considered towards the desired driving lane (230).

10. Driving method according to the preceding claim, wherein, if the desired driving lane (230) is not close to the lane (210) used by the motor vehicle (100), it is expected, after the vehicle has changed a first lane of traffic to approach the desired traffic lane (230), to repeat said steps a) to d) and the driving step.