Method for detecting a road element on a roadway.

Abstract

Method for detecting a road feature on a roadway. Method for detecting a road feature on a roadway, comprising a processing phase of a stream of images acquired by a camera (3), the processing phase comprising at least one iteration of: - a step (511) of determining a characteristic of a feature on an image, - a step (513) of segmenting the image so as to define an area of ​​the image which corresponds to the roadway, and - a step (514) of excluding the image from the processing if the feature is not located in the area. Figure 4.

Description

Title of the invention: Method for detecting a road element on a roadway.

[0001] The invention relates to a method for detecting a road feature on a roadway. The invention also relates to a method for managing a database of road features present on a roadway. The invention also relates to a system for detecting a road feature on a roadway. The invention also relates to a system for managing a database of features present on a roadway. The invention further relates to a database obtained by implementing the management method. The invention further relates to the use of such a database by a third-party vehicle. The invention further relates to a motor vehicle comprising such a management system and / or such a detection system. The invention also relates to a computer program implementing one of the aforementioned methods. Finally, the invention relates to a recording medium on which such a program is recorded.

[0002] For certain current and future motor vehicles (whether of the assisted driving or autonomous type), there is a need for these vehicles to have the most reliable and accurate possible knowledge of their environment. This knowledge must focus on certain of the most relevant characteristics of the environment, such as characteristics of road features, including road signs or irregularities in the road surface.

[0003] The object of the invention is to provide a system and a method for detecting road features present on a pavement, improving upon devices and methods known in the prior art. In particular, the invention makes it possible to implement a system and a method that are simple and reliable while using minimal resources to identify the road features present on a pavement.

[0004] According to the invention, a method allows the detection of a road element on a roadway. The method comprises a processing phase of a stream of images acquired by a camera, the processing phase comprising at least one iteration of: - a step of determining a characteristic of an element on an image, - a step of segmenting the image so as to define an area of ​​the image which corresponds to the roadway, and - a step of excluding the image from the processing if the element is not located in the area.

[0005] The image segmentation step may include the implementation of a deep learning algorithm.

[0006] The determination step and the segmentation step can take place at least partly simultaneously.

[0007] The road element may be a road sign affixed to the roadway.

[0008] The road element may be an irregularity in the road surface.

[0009] The processing phase may include a character recognition step applied to the road element.

[0010] The character recognition step may include the implementation of a deep learning algorithm.

[0011] The method may include a step of recording an effect of the road element on the vehicle passing over the road element.

[0012] The recording step may include a recording of accelerations and / or vibrations and / or noise.

[0013] According to the invention, a method allows for the management of a database of road elements present on a roadway, comprising: (i) a phase of establishing the database of road signs affixed to the roadway, the establishment phase comprising: - a step for detecting an element, including the implementation of the detection process defined previously, - a step to determine the position of the road sign, and - a step of recording at least one characteristic of the road element and its position in the database if these are not already recorded, and / or (ii) a phase of modification of the database of road signs affixed to the roadway, comprising: - a step involving the determination of a road element that must be detectable by an optical sensor at a given moment, - a step to verify the presence of the road element, - in the absence of the road sign, a step to delete the data of the road element.

[0014] The constitution phase and / or the modification phase can be implemented by a motor vehicle.

[0015] The constitution phase can be implemented by several motor vehicles, the recording step being implemented only if several vehicles detect the same road sign at the same position.

[0016] The modification phase can be implemented by several motor vehicles, the removal step being implemented only if several vehicles determine an absence of road sign.

[0017] According to the invention, a database is obtained by implementing the management process defined above.

[0018] The invention also relates to the use by a third-party motor vehicle of the database defined above.

[0019] The invention also relates to a detection system comprising hardware and / or software elements implementing the detection process defined above, in particular hardware and / or software elements designed to implement the detection process defined above.

[0020] The invention also relates to a management system comprising hardware and / or software elements implementing the management process defined above, in particular hardware and / or software elements designed to implement the management process defined above.

[0021] The invention also relates to a motor vehicle comprising a management system defined previously and / or a detection system defined previously.

[0022] According to the invention, a computer program product comprises program code instructions recorded on a computer-readable medium to implement the steps of one or both of the processes defined above when said program runs on a computer

[0023] According to the invention, a computer program product downloadable from a communication network and / or recorded on a data medium readable by a computer and / or executable by a computer, is characterized in that it includes instructions which, when the program is executed by the computer, lead the latter to implement one and / or the other of the processes defined above.

[0024] According to the invention, a computer-readable data storage medium on which a computer program is recorded includes program code instructions for implementing one and / or the other of the methods defined above.

[0025] According to the invention, a computer-readable recording medium includes instructions which, when executed by a computer, lead the computer to implement one and / or the other of the processes defined above.

[0026] The invention also relates to a signal from a data carrier, carrying the computer program product defined previously.

[0027] The attached drawing represents, by way of example, an embodiment of a motor vehicle according to the invention and an execution of a management method according to the invention.

[0028] Fig. 1 is a schematic representation of an embodiment of a motor vehicle according to the invention.

[0029] Fig. 2 is a schematic view of an embodiment of a management system 2 according to the invention.

[0030] Fig. 3 is a schematic view of an embodiment of a first processing block of a management system 2 according to the invention.

[0031] Fig. 4 is a schematic view of an embodiment of a second processing block of a management system 2 according to the invention.

[0032] An embodiment of a motor vehicle 1 according to the invention is described below with reference to [Fig. 1].

[0033] The motor vehicle 1 is, for example, a passenger vehicle or a commercial vehicle. However, the vehicle may be of any type. The motor vehicle is intended for use on the road network. The vehicle may be an autonomous vehicle or a vehicle equipped with a driver assistance system.

[0034] The motor vehicle 1 includes a detection system 29 for a road element present on a roadway, in particular: - a road sign affixed, in particular painted, to the roadway, and / or - an irregularity, in particular damage, to a road surface.

[0035] Road signs can be of all kinds, including numbers indicating speed limits, sequences of alphabetical characters indicating directions, dangers or instructions, directional arrows, stop marks, marks indicating an obligation to give way, hatching (zebra crossings, pedestrian crossings) or markings of lanes reserved for priority vehicles.

[0036] Irregularities can also be of different kinds. For example, they may be a hole created by the removal of part of the surface layer (wearing course and binder course). The hole may be deeper and penetrate the base course. Another example is the presence of a manhole cover that is more or less flush with the surface of the pavement.

[0037] The detection system 29 comprises: - an optical sensor 3, and - a computer 5 to process the data from the optical sensor 3.

[0038] The motor vehicle 1 includes a management system 2 for a database of road elements present on the roadway.

[0039] Management system 2 comprises: - the detection system 29, - a geographic positioning device 4, and - the computer 5 which also processes the data from the geographic positioning device 4 or another computer which also processes the data from the geographic positioning device 4.

[0040] Furthermore, the detection system 29 and / or the control system 2 may include a measuring element 28 for accelerations and / or vibration and / or noise. The measuring element 28 may include an inertial measurement unit and / or an accelerometer and / or a microphone.

[0041] Management system 2 generates and maintains an up-to-date map containing all road features present on the roadway, which are crucial information for road users to correctly position and maneuver their vehicles safely. This map can be created from the database mentioned previously. Map generation allows users to know where to turn and position their vehicles without compromising their safety or that of other road users. Map generation also informs road maintenance services so they can address road surface irregularities when they reach a certain level of severity.

[0042] The management system 2 preferably further includes a display element 6 for road features present on the roadway in front of the motor vehicle 1, such as a screen 6. Preferably, this display element is located on a dashboard inside the passenger compartment of the motor vehicle. The display may show the road feature before the driver can see it or even when the driver cannot see it. In the case of a vehicle with driver assistance, the display element 6 is advantageous. In the case of an autonomous vehicle, the display element 6 can be advantageous, but appears less necessary.

[0043] Management system 2 further includes: - a memory 7, and - possibly a wireless telecommunications component 8.

[0044] The memory allows for the storage of data relating to road elements present on the roadway. It therefore preferably contains, for each road sign affixed to the roadway: - information regarding the nature of the road sign, and - geographical position information for the road sign, including GPS position information for the road sign.

[0045] It therefore preferably contains for each irregularity of the roadway: - information on the nature of the irregularity (for example manhole, pothole, crack, groove), and - information on the geographical position of the road element, in particular GPS position information of the road element.

[0046] Memory 7 contains the database of road elements present on the roadway.

[0047] The memory 7 can be located in the motor vehicle 1. In this case, it can be connected by wire to the computer 5. Alternatively, the memory can be located outside the motor vehicle 1, for example in a remote server. In this case, the management system 2 includes the wireless telecommunications element 8 which enables communication between the computer and the memory.

[0048] Advantageously, the display can also show the distance between the motor vehicle and the next road feature. This distance can be indicated by using different display colors for the road feature. For example: - a first color indicates a distance of less than 10 m, - a second color indicates a distance of less than 50 m, and - a third color indicates a distance of less than 100 m. Alternatively, the distance can be indicated by displaying a numerical value.

[0049] Preferably, the display element 6 filters or highlights the road features on the roadway that are relevant to the motor vehicle 1, taking into account its positioning.For example, if motor vehicle 1 is on a roadway with multiple lanes, the display element may only show or highlight road features relevant to the lane on which motor vehicle 1 is located.

[0050] Advantageously, the optical sensor 3 is a camera 3 or comprises at least one camera 3 capable of acquiring images suitable for processing by the computer 4. Preferably, the optical sensor 3 is a monocular camera 3. The optical sensor 3 is preferably positioned behind the windshield or at the level of a grille at the front of the motor vehicle. The optical sensor 3 is further arranged and configured to take at least some images of the environment in front of the motor vehicle. The optical sensor 3 is therefore arranged and configured to allow the detection of road signs affixed to the roadway or irregularities in the road surface.

[0051] The geographic positioning device 4 may include a GPS location device 4. The geographic positioning device 4 may also optionally include a magnetometer for determining the orientation of the motor vehicle.

[0052] Calculator 5 includes: - a module 51 for the optical detection of a road element, - a module 52 for determining the position of the road element, and - a module 53 for recording at least one characteristic of the road element and its position in the database if these are not already recorded, and / or - a module 54 for determining a road element that must be detectable by an optical sensor at a given moment, - a module 55 for verifying the presence of the road element, and - a module 56 for deleting the data of this road element, in case of absence of the road element in front of the motor vehicle.

[0053] The detection system 29 comprises all the hardware and / or software elements 3, 5, 28 implementing or governing the detection method that is the subject of the invention. These various elements may include software modules.

[0054] The management system 2 comprises all the hardware and / or software elements 3, 4, 5, 6, 7, 8, 28, 29 implementing or governing the process of managing the database of road signs affixed to a roadway. These various elements may include software modules.

[0055] An execution method for managing the database of road features present on a roadway is described below. The management method can also be viewed as a method for operating the management system or the motor vehicle comprising such a management system.

[0056] The process comprises: - a phase of building the database of road signs affixed to the roadway and / or - a phase of modifying the database of road signs affixed to the roadway.

[0057] The constitution phase is implemented in particular when a motor vehicle 1 as described above arrives near a road element present on the roadway (this road element not being recorded in the database).

[0058] In a first detection step, an execution method for detecting a road feature present on the roadway is implemented. The detection method can also be viewed as an operating method of the detection system or of the motor vehicle comprising such a detection system. In this step, a video stream produced by the optical sensor 3 is continuously transmitted to the computer 5. The optical road feature detection module 51 allows the identification of a road feature within this stream. In particular, module 51 allows the identification of a characteristic of the road feature, such as its nature or extent (apparent surface area on the ground). This step is described in more detail below.

[0059] In a second determination step, the position of the road element is determined. To do this, the position provided at the output of the device can be read, for example. Geographic positioning 4 of the motor vehicle at the moment the motor vehicle 1 passes over the road element, or the geographic position of the road element can be calculated using: - the geographical position of the motor vehicle 1, and - the position of the road element on the images from optical sensor 3 (determining the position of the road element relative to motor vehicle 1), the orientation of motor vehicle 1 can also be advantageously used. This second step is implemented by the determination module 52.

[0060] Preferably, in the case of a road surface irregularity, in a third step, at the moment when the motor vehicle 1 passes over the road surface irregularity, the effect of the irregularity on the motor vehicle is recorded. For this purpose, vibrations and / or accelerations and / or noise in the motor vehicle can be recorded at the moment the motor vehicle 1 passes over the road surface irregularity. For this purpose, the acceleration and / or vibration and / or noise measuring element 28 is used, for example.

[0061] In a fourth recording step, the following is recorded: - at least one characteristic of the element, including its nature, extent, or degree of severity (in the case of a road surface irregularity), and - its geographical location,

[0062] in the database if they are not already recorded, associated with the data recorded during the third step if it took place. Otherwise (if at least one characteristic of the road element and the geographical position are already recorded in the database), the database is not modified. However, if the geographical position is already recorded, but at least one recorded characteristic does not correspond to at least one characteristic determined in the first step, the recorded data is replaced (or overwritten) with the at least one characteristic determined in the first step. The fourth step is implemented by the recording module 53.

[0063] These first, second, fourth and possible third steps are preferably iterated continuously during the operation of the motor vehicle 1.

[0064] The modification phase is implemented in particular when a motor vehicle 1 as described above arrives near a position where, according to the database, there should be a road element present on the roadway.

[0065] In a fifth determination step, it is determined which road element must be detectable by the optical sensor 3 in front of the vehicle. This step is implemented by the determination module 54, for example by querying memory 7.

[0066] In a sixth verification step, the actual presence of the road element is verified. This step is implemented by the verification module 55.

[0067] If the presence of the road element could not be confirmed in the previous step, a seventh deletion step is performed, deleting from the database the data relating to the road element whose presence could not be confirmed. If the presence of the road element is verified, the database is not modified. This seventh step is implemented by the deletion module 56.

[0068] These fifth, sixth and seventh steps are preferably iterated continuously during the driving of the motor vehicle 1.

[0069] Management system 2 can also be schematically represented as in [Fig.2].

[0070] The raw images produced by the optical sensor 3 are transmitted, in a The first branch consists of a 510 block for recognizing road signs. The structure of the 510 block is described in more detail below. This recognition block analyzes each image and emits a positive recognition signal for each image where a road element present on the roadway is recognized, and a negative signal for each image where no road element is recognized. The positive signal advantageously contains at least one characteristic of the road element, such as its nature or surface area.

[0071] Next, a follow-up block 520 allows observation of the sequences of signals emitted by the block 510 and avoids false detection signals.

[0072] In a 580 block, it is tested whether the counter has reached a predefined value. If so, it proceeds to a 550 block. If not, it proceeds to a 530 block in which it waits for the counter to reach the predefined value before proceeding to the 550 block.

[0073] The raw images produced by the optical sensor 3 are also transmitted, in a second branch, to a distance estimation block 540 in which deep learning artificial intelligence is implemented to estimate the distance separating the motor vehicle 1 from all the elements appearing in the images, and therefore from a road feature present on the roadway and appearing in the images. For example, in this block 540, a distance is associated with each pixel or group of pixels in the image, the distance being the distance between the motor vehicle 1 and the portion of the object whose pixel or group of pixels is the image.

[0074] In block 550, the data from block 580 and block 540 are combined to determine the distance of the motor vehicle 1 to the road feature on the road that has been detected and validated. To do this, for example, the average distance between the motor vehicle 1 and each pixel or group of pixels representing a portion of the road feature on the road can be calculated. In this block 550, a distance and at least one characteristic of the detected road feature are therefore associated, such as its type or extent.

[0075] Next, in block 560, the position of the road element present on the roadway is determined. To do this, the distance data separating the motor vehicle 1 from the road element, determined in block 550, and a geographic position data for the vehicle provided by the geographic positioning device 4 are used. The orientation of the motor vehicle can also be used for this purpose.

[0076] Once the position of the road element is detected, one purpose of the management system being to create a database, in block 590, the following data is recorded: - geographical position, and - of nature and / or extent and / or effect on the motor vehicle (in the case of an irregularity in the road surface), of the road element present on the roadway in memory 7.

[0077] It should be noted that this recording only takes place if it is not already present in memory 7, that is to say: - if no road element was currently associated with the geographical position in memory 7, or - if a road feature of a different nature or extent was currently associated with the geographical location in memory 7 (due to a change in signage, repairs, or damage to a road surface irregularity, for example). The nature or extent of the former road feature is then erased.

[0078] In a block 570, using the geographic positioning device 4, the geographic position of the vehicle can be known and thus it can be determined, in real time, which road elements present on the roadway are in front of the motor vehicle 1, even if the road element is not (yet) visible to the driver or to the optical sensor 3.

[0079] An embodiment of block 570 is described in more detail below with reference to [Fig.3].

[0080] A first sub-block 571 compares: - the road element possibly recognized by motor vehicle 1 in real time, at - the information contained in memory 7 and indicating the road element that must be located and visible in front of the vehicle in real time.

[0081] If a match is found, knowing that the motor vehicle 1 is close to the road element, a sub-block 573 is entered in which the nature or extent of the road element is determined. This information regarding the nature or extent is then displayed by the display element 6 or used directly by the motor vehicle 1.

[0082] In case of a discrepancy, the system proceeds to a sub-block 572 in which it determines whether a road feature is detected by using the optical sensor in real time. If so, it is known that the motor vehicle 1 is close to the road feature, the information provided by the optical sensor 3 is prioritized, and the system proceeds to a sub-block 573 in which the nature or extent of the road feature is determined. This information regarding the nature or extent is then displayed by the display element 6 or used directly by the motor vehicle 1. If this is not the case, it is concluded that the vehicle must be further away from the next road feature.

[0083] An embodiment of block 510 is also described in more detail below with reference to [Fig.4].

[0084] In this block 510, the raw images are provided to two parallel processing branches in which deep learning algorithms are implemented.

[0085] In a first branch, a sub-block 511 enables the recognition and determination of at least one characteristic of a road element whose representation is present on a raw image, using a neural network trained to recognize such elements. This at least one characteristic is, in particular, the nature of the road elements present on the roadway, the extent of the road element, and / or its distance.

[0086] In some cases, road features include one or more alphanumeric characters. This is the case, for example, when stop signs, speed limit signs, reserved lane signs, or directional signs (mentioning city names) are affixed to the roadway. In order to fully understand the nature of the road feature, a character recognition sub-block 512 is implemented. Preferably, this sub-block 512 implements a deep learning algorithm. The character recognition processing is preferably performed on only a portion of the image where a road feature has been recognized, and not on the entire image. Indeed, in addition to the unnecessary use of resources, processing the entire image could lead to the recognition of irrelevant character strings that might be located in other areas of the image.In the case of detecting irregularities in the road surface, this sub-block 512 is not implemented.

[0087] In a second branch, a sub-block 513 performs segmentation of the raw image in order to distinguish the roadway from other elements visible in the raw image that are not located on the roadway, such as a sidewalk or shoulder, or any element located beyond the sidewalk or shoulder. Preferably, this sub-block 513 implements a deep learning algorithm.

[0088] Thus: - the recognition and determination of at least one characteristic of a road element, and - the segmentation of the raw image, are carried out at least partially simultaneously.

[0089] In particular: - the recognition and determination of at least one characteristic of a road element can be implemented throughout the segmentation of the raw image, and - the segmentation of the raw image can be implemented throughout the recognition and determination of at least one characteristic of a road element.

[0090] Using the results from both branches, in sub-block 514, it is tested whether the road feature identified by sub-block 511 (which recognizes and determines at least one characteristic of an identified road feature) is located on the roadway delimited by sub-block 513 (which segments the raw image). If so, in sub-block 516, the validity of the detected signal is confirmed and the information can be transmitted to block 520 (described in connection with [Fig. 2]). If not, in sub-block 515, the detected road feature is ignored. In other words, an image exclusion step is implemented if the feature is not located in the area of ​​the image corresponding to the roadway.

[0091] Preferably, the invention does not apply to road signs separating traffic lanes.

[0092] The database obtained by implementing the method described above can advantageously be used by a third-party vehicle, in particular a driver-assistance vehicle that does not have an optical sensor, but has a display element for a road feature affixed to the roadway in front of the third-party vehicle, such as a screen 6. Preferably, this display element is located on a dashboard inside the passenger compartment of the third-party vehicle. The display can show the road feature before the driver can see it or even when the driver cannot see it.

[0093] Advantageously, in this third-party vehicle, the display of the distance separating the motor vehicle and the road element can be carried out as described above.

[0094] Preferably, the display element 6 filters or highlights road signs affixed to the roadway that are relevant to the third-party vehicle, taking into account its position. For example, if the third-party vehicle is on a roadway with multiple lanes, the display element may only display or highlight the road signs relevant to the lane in which the third-party vehicle is located.

[0095] In other words, the method and system according to the invention allow vehicles equipped with cameras to detect road signs affixed to the roadway in order to create enhanced maps of the positions of these signs, which can be used by a maximum number of road users to improve safety. In particular, this data can be used to alert drivers to dangerous situations so that they can be more vigilant.

[0096] To achieve this, the solutions according to the invention use, for example, a camera and a GPS device to detect, recognize, and position road signs affixed to the roadway. By further utilizing artificial intelligence solutions (Deep Learning), it is possible, with a simple monocular camera, to obtain three-dimensional (3D) information from a large number of road signs affixed to the roadway and to perform a thorough analysis of these signs for perfect recognition of their nature. This improves the vehicle's awareness of its surroundings and allows other road users to utilize this knowledge to enhance safety.

[0097] The solutions according to the invention further improve the visibility of road signs affixed to the roadway when these signs are difficult to see, particularly due to poor visibility conditions (night, fog, rain, snow, sunrise, sunrise / sunset, etc.) and / or because the markings of the road sign are damaged, notably partially erased or partially covered. Such damage may be due to roadworks or wear and tear.

[0098] The presence of several road signs placed close together in the same area of ​​the roadway can result in some information not being perceived by a driver. This is the case, for example, at multi-lane intersections where the driver receives road information both through road markings on the ground and vertical signs. Taking all this information into account in different areas of the driver's vision is difficult. The solutions according to the invention make it possible to duplicate the display of road signs affixed to the ground in another area of ​​the driver's field of vision to overcome this drawback.

[0099] Other situations, particularly in urban areas, can affect a road user's ability to detect information on the road surface. For example, preceding vehicles may stop at road signs, thus obscuring them from the driver's view. The solutions described above can again provide assistance in these situations.

Claims

Demands

1. Method for detecting a road element on a roadway, comprising a processing phase of a stream of images acquired by a camera (3), the processing phase comprising at least one iteration of: - a step (511) of determining a characteristic of an element on an image, - a step (513) of segmenting the image so as to define an area of ​​the image which corresponds to the roadway, and - a step (514) of excluding the image from the processing if the element is not in the area.

2. A method according to the preceding claim, characterized in that the image segmentation step (513) includes the implementation of a deep learning algorithm.

3. A method according to any one of the preceding claims, characterized in that the determination step (511) and the segmentation step (513) take place at least partly simultaneously.

4. A method according to any one of the preceding claims, characterized in that the road element is a road sign affixed to the roadway.

5. A method according to any one of claims 1 to 3, characterized in that the road element is an irregularity in the pavement surface.

6. Method according to claim 4, characterized in that the processing phase includes a character recognition step (512) applied to the road element.

7. A method according to claim 5, characterized in that the method comprises a step of recording an effect of the road element on the vehicle passing over the road element.

8. A method according to the preceding claim, characterized in that the recording step includes a recording of accelerations and / or vibrations and / or noise.

9. A method for managing a database of road features present on a roadway, comprising: (i) a phase of constructing the database of road signs affixed to the roadway, the construction phase comprising: - a step of detecting a feature comprising the implementation of the detection method according to any one of claims 1 to 8, - a step of determining the position of the road sign, and - a step of recording at least one characteristic of the road element and its position in the database if these are not already recorded, and / or (ii) a phase of modifying the database of road signs affixed to the roadway, comprising: - a step of determining a road element that must be detectable by an optical sensor at a given time, - a step of verifying the presence of the road element, - in the event of the absence of the road sign, a step of deleting the data of the road element.

10. Management method according to the preceding claim, characterized in that: - the building phase is carried out by a motor vehicle, and / or - the modification phase is carried out by a motor vehicle.

11. Management method according to claim 9 or 10, characterized in that: - the constitution phase is carried out by several motor vehicles, the recording step being carried out only if several vehicles detect the same road sign at the same position, and / or - the modification phase is carried out by several motor vehicles, the deletion step being carried out only if several vehicles determine an absence of a road sign.

12. Database obtained by implementing the method according to any one of claims 9 to 11.

13. Detection system (29), the detection system comprising hardware and / or software elements (3, 5, 28) implementing the method according to any one of claims 1 to 8, in particular hardware and / or software elements (3, 5, 28) designed to implement the method according to any one of claims 1 to 8.

14. Management system (2) of a motor vehicle (1), the management system comprising hardware and / or software elements (3, 4, 5, 6, 7, 28, 29) implementing the method according to any one of claims 9 to 11, in particular hardware elements (3, 4, 5, 6, 7, 28, 29) and / 16 or software designed to implement the process according to any one of claims 9 to 11.

15. Motor vehicle (1) comprising a management system (2) according to the preceding claim and / or a detection system (29) according to claim 13.

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