WO2024052561A1

WO2024052561A1 - Method for detecting an upcoming collision, method for calibrating a collision detection system, and associated motor vehicle

Info

Publication number: WO2024052561A1
Application number: PCT/EP2023/074800
Authority: WO
Inventors: Norbert Rossello
Original assignee: Ampere S.A.S.
Priority date: 2022-09-09
Filing date: 2023-09-08
Publication date: 2024-03-14
Also published as: FR3139532A1

Abstract

The invention relates to a method for detecting an upcoming collision between a motor vehicle (10) and at least one other user (20, 30, 40, 50, 60, 70) present in the environment of the motor vehicle, the motor vehicle comprising a computer equipped with a communication unit and the other user comprising a mobile terminal (21, 22, 23, 24, 25, 26, 31, 41, 51, 61, 71) configured to communicate with the communication unit of the computer, the method comprising the following steps, at two successive instants: - detecting the presence of the other user in the environment of the motor vehicle by transmitting, using the communication unit of the computer, a wireless communication signal,- receiving, using the communication unit of the computer, a response signal transmitted by the other user following the reception of the wireless communication signal, - determining a location datum in relation to the other user by means of characteristics of the response signal, and - detecting an upcoming collision between said motor vehicle and the other user by determining a risk of collision indicator on the basis of the location data determined at the two successive instants.

Description

Title of the invention: Method for detecting an upcoming collision, method for calibrating a collision detection system and associated motor vehicle

Technical field of the invention

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

[0002] The invention relates more particularly to a method for detecting an upcoming collision between a motor vehicle and another user present in the environment of the motor vehicle.

[0003] It also relates to a method for calibrating a collision detection system between a motor vehicle and another user present in the environment of the motor vehicle.

[0004] The invention finally relates to an associated motor vehicle.

State of the art

[0005] In order to secure motor vehicles, they are currently equipped with driver assistance systems (or ADAS for “Advanced driver-assistance systems” according to the acronym of Anglo-Saxon origin commonly used) or even highly automated driving systems.

[0006] Among these systems, we know in particular automatic emergency braking systems (better known by the abbreviation AEB, from English “Automatic Emergency Braking”), designed to avoid any collision with obstacles located in the lane. taken by the vehicle, by simply acting on the conventional braking system of the motor vehicle.

[0007] We also know automatic avoidance systems (better known by the abbreviation AES, from the English “Automatic Evasive Steering” or “Automatic Emergency Steering”) which make it possible to avoid the obstacle by diverting the vehicle from its trajectory, by acting on the direction of the vehicle.

[0008] These systems make it possible, in general, to detect an imminent collision with another motor vehicle, to alert the driver and to activate, if necessary, the braking system until the vehicle comes to a complete stop. automobile.

[0009] To enable this detection, these systems generally include sensors equipped with radars and/or lasers (such as lidars, for “Easer Imaging Detection And Ranging”) and/or image acquisition sensors such as cameras. These various sensors are positioned at the front of the motor vehicle (for example behind the bumper) or at the front of the dashboard, in the passenger compartment of the vehicle. tomobile. The analysis of the data from these sensors makes it possible to locate other vehicles in the environment of the motor vehicle of interest and to assess a risk of collision with one of them.

[0010] However, the different sensors used have drawbacks, particularly in the event of unfavorable weather conditions, for example in the event of foggy or rainy weather.

[0011] Indeed, the water droplets present in the air in foggy or rainy weather diffuse or deflect the laser beam emitted by a lidar, which then makes the analysis of the reflected beams difficult for the detection of objects. present in the environment of the motor vehicle. Likewise, drops of water present on a windshield can obscure all or part of the field of vision of an acquisition sensor positioned in the passenger compartment of the motor vehicle. Under these conditions, the detection of other road users in the environment of the motor vehicle is therefore difficult or even impossible.

[0012] Furthermore, in the event of a malfunction and/or unavailability of the detection system in the motor vehicle, the driver can only rely on his vigilance (and his visual acuity) to avoid a possible collision.

Presentation of the invention

[0013] In order to remedy the aforementioned drawbacks, the present invention proposes to improve the detection of a possible collision, whatever the weather conditions or in the event of malfunction or unavailability of detection systems in the motor vehicle.

[0014] More particularly, according to the invention, a method is proposed for detecting an upcoming collision between a motor vehicle and at least one other user present in the environment of the motor vehicle, the motor vehicle comprising a computer equipped with a communication unit and the other user comprising a mobile terminal configured to communicate with the communication unit of the computer, the method comprising, at two successive times, steps of:

- detection of the presence of the other user in the environment of the motor vehicle by emission, by the communication unit of the computer, of a wireless communication signal,

- reception, by the computer communication unit, of a response signal transmitted by the other user following reception of the wireless communication signal,

[0015] - determination of location data of the other user by means of characteristics of the response signal, and

- detection of an upcoming collision between said motor vehicle and the other user reader by determining a collision risk indicator based on the location data determined at the two successive times.

[0016] Thus, according to the present invention, the detection of a possible collision is carried out using wireless communications which can be established between the computer of the motor vehicle and other road users. This process is particularly simple to implement because it relies on the establishment of wireless communications with mobile terminals commonly used today.

[0017] Furthermore, these wireless communications can be implemented regardless of weather conditions. Furthermore, this detection does not rely on the use of sensors present in the vehicle, the possible malfunctions or unavailability of which could be detrimental to the detection of possible collisions.

[0018] Other advantageous and non-limiting characteristics of the detection method according to the invention, taken individually or in all technically possible combinations, are as follows:

- the collision risk indicator is determined by calculating a rate of increase between the location data determined at the two successive times;

- each determined location data comprising a relative distance between the motor vehicle and the other user, in the collision detection step, sub-steps are provided for: a) determination of a sign of the indicator of risk of collision, and b) comparison of at least one of the relative distances determined with a predetermined distance threshold, an upcoming collision being detected when the collision risk indicator is negative and said relative distance is less than said threshold of predetermined distance;

- the predetermined distance threshold is less than 15 meters;

- at each successive moment, a step of identifying the other user is provided by an identification element transmitted in said response signal;

- steps are planned to:

[0019] al) encryption of said identification element, and bl) storage of said encrypted identification element in a memory of said computer;

- before determining the collision risk indicator, a step of smoothing the location data is provided;

- the step of smoothing the location data is carried out by determining an exponential moving average; - wireless communication is established according to the Bluetooth® standard; And

- wireless communication is established using the Ultra Wide Band modulation technique.

[0020] The invention also relates to a method for calibrating a collision detection system between a motor vehicle and at least one other user present in the environment of the motor vehicle, said detection system comprising at least one collision sensor. remote sensing and/or imaging and a control unit, the motor vehicle comprising a computer provided with a communication unit, the method comprising steps of:

- acquisition, by the remote sensing and/or imaging sensor, of data concerning the environment of the motor vehicle,

- determination of location data for the other user based on the acquired data and taking into account processing parameters of the control unit of the detection system,

- obtaining the location data of said other user by implementing the detection method described above,

- determination of a difference between the determined location data and the obtained location data, then if said difference is greater than a predetermined threshold,

- updating of control unit processing parameters

[0021] The invention also relates to a motor vehicle comprising a computer configured to implement a collision detection method as previously introduced.

Of course, the different characteristics, variants and embodiments of the invention can be associated with each other in various combinations to the extent that they are not incompatible or exclusive of each other. Detailed description of the invention

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

[0024] In the attached drawings:

[0025] [Fig-1] represents a schematic top view of a motor vehicle adapted to implement a method according to the invention;

[0026] [Fig.2] is a schematic top view of the motor vehicle and other road users present in the environment of the motor vehicle;

[0027] [Fig.3] represents, in flowchart form, an example of a method for detecting a collision between the motor vehicle and another compliant road user to invention; And

[0028] [Fig.4] represents, in flowchart form, an example of a method for calibrating a collision detection system according to the invention.

[0029] In [Fig.1], there is shown an automobile vehicle 10 adapted to implement the invention.

[0030] This is a car. Alternatively, it could be another type of vehicle (truck, motorcycle, etc.).

[0031] Here, this vehicle 10 conventionally comprises a passenger compartment in which there are in particular a seat for the driver of the vehicle, a dashboard 14 with a display screen 13, and a steering wheel 12.

This vehicle 10 comprises a powertrain, a braking system and a steering system allowing the vehicle to turn (not visible in the figure). Conventionally, the steering system includes an electronically controllable power steering actuator, the powertrain includes an electronically controllable motor control actuator, and the braking system includes an electronically controllable brake actuator.

[0033] The vehicle 10 also comprises an electronic and/or computer processing unit (hereinafter called computer 11) comprising at least one microprocessor or microcontroller, at least one memory and input and output interfaces.

[0034] Thanks to its input interfaces, the computer 11 is adapted to receive different input data, which comes from sensors or third-party computers.

[0035] For example, among these sensors, it is for example provided:

- a device such as a front camera and/or a side camera, making it possible to identify the position of the motor vehicle 10 in relation to its lane, and

- a device such as a RADAR remote detector and/or a LIDAR remote detector, making it possible to detect the edges of the road.

[0036] These different sensors can for example be used as part of a collision detection system 15 optionally fitted to the motor vehicle 10. The data acquired by these different sensors are for example processed and analyzed by a control unit 17 included in this detection system 15.

[0037] Thanks to its output interfaces, the computer 11 is adapted to control the display screen 13, the power steering actuator, the engine control actuator, and the braking actuator.

[0038] Thus, the computer 11 is adapted to implement driving assistance functions and/or automated driving functions (thanks to which the motor vehicle 10 can move in traffic autonomously, without intervention from the driver ).

[0039] Thanks to its memory, the computer 11 memorizes a computer application, consisting of computer programs comprising instructions whose execution by the computer allows the implementation of the monitoring method described below.

[0040] Finally, in the context of the present invention, the computer 11 comprises a communication unit 11A configured to communicate, via wireless communication, with other electronic equipment present in the environment of the motor vehicle 10. For example , the communication unit 1 IA can enter into communication with a mobile terminal 21, 22, 23, 24, 25, 26, 31, 41, 51, 61, 71 carried by another user 20, 30, 40, 50, 60, 70 of the road ([Fig.2]).

[0041] This mobile terminal 21, 22, 23, 24, 25, 26, 31, 41, 51, 61, 71 is for example an intelligent mobile telephone (or “smartphone” according to the commonly used Anglo-Saxon designation of origin). used).

[0042] Alternatively, it could be another type of mobile terminal, for example a connected watch, a pair of connected glasses, a digital tablet or even another communication unit of another motor vehicle.

[0043] Here the wireless communication is for example of the Bluetooth® type. The present invention finds a particularly advantageous application in the context of a low energy Bluetooth® connection (or BLE for “Bluetooth Low Energy” according to the commonly used acronym of Anglo-Saxon origin).

[0044] This type of wireless communication is particularly advantageous because it consumes very little energy for the transmission of signals.

[0045] Alternatively, the wireless communication can be of the Ultra Wide Band (or UWB for “Ultra Wide Band”) modulation type.

[0046] Of course, other communication protocols could also be used.

[0047] Generally speaking, in the present invention, it is considered that the motor vehicle 10 is traveling on a traffic lane 100A. In [Fig.2], the motor vehicle 10 is shown traveling on the traffic lane 100A leading to an intersection 200 with other traffic lanes 100B, 101A, 101B, 102A, 102B, 103A, 103B.

[0048] As shown in [Fig.2], other users 20, 30, 40, 50, 60, 70 of the road are present on these traffic lanes 100B, 101A, 101B, 102A, 102B, 103A, 103B. These include, for example, other vehicles such as a bus 20, a person on a bicycle 60, a two-wheeler 30, a truck 40, a pedestrian 50 or another car 70.

[0049] Here, each other user 20, 30, 40, 50, 60, 70 of the road is equipped with a mobile terminal 21, 22, 23, 24, 25, 26, 31, 41, 51, 61, 71 In the bus 20, we consider for example that several people are each equipped with a mobile terminal 21, 22, 23, 24, 25, 26.

[0050] The present invention relates to a method for detecting upcoming collisions between the motor vehicle 10 and one or more of the other users 20, 30, 40, 50, 60, 70 of the road. This method aims to make it possible to detect a possible next collision (upstream, before it occurs) from wireless communications established between the motor vehicle 10 and at least one other user 20, 30, 40, 50, 60, 70 of the road.

[0051] More particularly, thanks to the wireless communications established between the communication unit 11A of the computer 11 of the motor vehicle 10 and each mobile terminal 21, 22, 23, 24, 25, 26, 31, 41, 51, 61, 71 equipping one of the other users 20, 30, 40, 50, 60, 70 of the road, the method according to the invention allows at any time to locate each of the other users 20, 30, 40, 50, 60, 70 (simultaneously). Then by following the relative movement of each of the other users 20, 30, 40, 50, 60, 70 in relation to the motor vehicle 10, the method makes it possible to evaluate the risk of a future collision for the motor vehicle 10.

[0052] For this, the detection method is implemented iteratively, at regular time intervals, during the movement of the motor vehicle 10. This method is for example executed in a loop between the starting and stopping of the motor vehicle 10.

[0053] As emerges from the description which follows and which is represented, in the form of a flowchart, in [Fig.3], certain steps of the process are therefore repeated in a loop at regular time steps. This time step is for example between 5 and 100 milliseconds, preferably of the order of 10 milliseconds.

As shown in [Fig.3], the process begins in step E2 of initializing a time variable t. This time variable t corresponds to the start time of implementation of the process. For example here, this time variable t is initialized at time t ₀ . We will consider here that this instant t ₀ corresponds to an instant distinct from the moment when the vehicle 10 is started.

The process then continues in step E4. During this step, the communication unit 11 A of the computer 11 of the motor vehicle 10 emits a plurality of wireless communication signals in all directions around the motor vehicle 10. In other words, the communication unit 11A scans the environment surrounding the motor vehicle 10 by transmitting this plurality of wireless communication signals. This plurality of wireless communication signals aims to detect the presence of one or more users 20, 30, 40, 50, 60, 70 in the environment of the motor vehicle 10.

[0056] Each mobile terminal 21, 22, 23, 24, 25, 26, 31, 41, 51, 61, 71 equipping the other users 20, 30, 40, 50, 60, 70, which receives the transmitted communication signal by the communication unit 11 A, transmits, in response, a response wireless communication signal (step E4).

[0057] In step E6, this response wireless communication signal is received by the unit of communication 1 IA of the computer 11. At the end of this step, the computer 11 therefore has a list of all the other users present in the environment of the motor vehicle 10 (having issued a response to the communication signal without thread).

[0058] It can be noted here that the motor vehicle 10 can also include mobile terminals (not shown) which could possibly receive the communication signal transmitted by the computer 11 and transmit in return a response wireless communication signal. However, these mobile terminals have for example been identified by the computer 11, prior to the implementation of the method. They are therefore not considered in the present invention.

[0059] More precisely, in step E8, the computer 11 identifies each other user 20, 30, 40, 50, 60, 70 using the response wireless communication signal which includes an identification element associated with the other user 20, 30, 40, 50, 60, 70 concerned.

[0060] Indeed, in the context of the wireless communication established between the communication unit 11A and each other user 20, 30, 40, 50, 60, 70, each other user 20, 30, 40, 50, 60 , 70 presents a unique identification element associated with it (also called UUID for “Universal Unique Identifier”). The computer 11 receives this identification element associated with each other user 20, 30, 40, 50, 60, 70 upon reception of the response wireless communication signal.

[0061] This identification element allows the computer 11 to follow at any time the other user 20, 30, 40, 50, 60, 70 concerned.

[0062] As shown in [Fig.3], the process continues in step E10, during which the computer 11 proceeds to encrypt each identification element received. Indeed, in order to ensure protection of the data of other users 20, 30, 40, 50, 60, 70, the identification element of each other user 20, 30, 40, 50, 60, 70 is not not manipulated as such by the computer 11.

[0063] The encryption of the identification element is for example implemented by application of a cryptographic hash function using a secret encryption key. This cryptographic hash function is for example a keyed hash message authentication code of the HMAC-SHA-1 type (with HMAC for “keyed-hash message authentication code”).

The encrypted identification element is then stored in the memory of computer 11 (step E12).

The process continues in step E14. During this step, the calculator 11 determines location data associated with each other user 20, 30, 40, 50, 60, 70. Thanks to the established wireless communication, this location data is deduced from the characteristics of the communication signal wireless received, by the computer 11, for each other user 20, 30, 40, 50, 60, 70. [0066] For example, in the context of low energy Bluetooth® type wireless communication, the location data is deduced from the power data of the response signal (or RSSI for “Received Signal Strength Indication”) as well as of the angles of arrival (“Angle of Arrivai”) and departure (“Angle of Departure”) of this signal.

[0067] In practice here, the location data associated with each other user 20, 30, 40, 50, 60, 70 is represented by the spherical coordinates of this other user 20, 30, 40, 50, 60, 70 in the mark of the motor vehicle 10.

[0068] In general, as shown in [Fig.l], we define, with respect to the motor vehicle 10, an orthonormal vehicle reference frame (in Cartesian coordinates) characterized by an origin O located for example in the middle of the front axle, a longitudinal axis

[0069] The spherical coordinates are then defined, relative to this orthonormal reference frame with (for each other user i among the other users 20, 30, 40, 50, 60, 70): P, the radial distance defined as the distance between the motor vehicle 10 and the other user i concerned, 0 _; , the polar angle defined as the offset angle, in the road plane, between the motor vehicle 10 and the other user i concerned and q>_; , the azimuthal angle defined as an angle characterizing a difference in altitude between the motor vehicle 10 and the other user i concerned.

[0070] According to the context of the present invention, the azimuthal angle q>_; is weak and poorly characterizes the location of other users 20, 30, 40, 50, 60, 70.

[0071] These spherical coordinates are a function of time. Thus, at time t ₀ , in step E14, for each other user, the computer 11 determines the spherical coordinates of each other user i in relation to the motor vehicle 10.

[0072] Alternatively, the location data could be represented by Cartesian coordinates.

[0073] Finally, at the end of step E14, the computer 11 has location data, at time t ₀ , for each other user 20, 30, 40, 50, 60, 70 present in the environment of the motor vehicle 10. In particular, from each determined location data, the calculator 11 deduces the relative positioning (front, rear, right, left) of each other user 20, 30, 40, 50, 60, 70 by relation to the motor vehicle 10.

[0074] In step E16, the calculator 11 implements a step of smoothing the location data. This smoothing step has the advantage of making it possible to overcome occasional deviations or to minimize the noise resulting from the raw determination of the location data.

[0075] This smoothing step corresponds for example to first-order low-pass filtering of the location data. [0076] For example, this smoothing step is carried out by a method of determining an exponential moving average of the radial distance.

[0077] In the context of this method, the moving average r _avg. of the radial distance is given by the following expression:

[0078] [Math.l]

[0079] with r _; (t ₀ ) the radial distance determined between the motor vehicle 10 and the other user i concerned determined at the current time t ₀ , r _avg. (t ₀ -At) the moving average determined at the previous time, r _{avg i} (t ₀ ) the moving average determined at the current instant and has a smoothing constant defined by the following expression:

[0080] [Math.2] a U = — N+l

[0081] with N an integer to choose according to the desired smoothing precision.

[0082] It should be noted that the moving average r _{avg i} (to-At) at the very first instant of implementation of the method is for example equal to the first determined value of the radial distance between the motor vehicle 10 and the other user i concerned.

[0083] As shown in [Fig.3], the process continues in step El 8, during which the time variable t is incremented by a predetermined time step. The time at which the following steps are implemented (after incrementation) is called “current time” in the following.

[0084] Steps E20 to E32 are respectively the same as steps E4 to El 8 described previously. They aim to allow the determination of another location data for each other user 20, 30, 40, 50, 60, 70, at the current time.

[0085] Thus, in step E30, and similarly to step E14 described previously, the calculator 11 determines another location data associated with each other user 20, 30, 40, 50, 60, 70 and corresponding to its location at the current time.

[0086] For example, the calculator 11 determines the spherical coordinates of each other user 20, 30, 40, 50, 60, 70 at the current time.

[0087] Thus, at the end of step E30, the computer 11 has, for each other user 20, 30, 40, 50, 60, 70, two location data determined at two successive times. These two location data determined at two successive times will make it possible to evaluate the possibility that a collision between the motor vehicle 10 and at least one of the other users 20, 30, 40, 50, 60, 70 of the road will occur. .

[0088] Similar to step E16 described previously, in step E32, the computer 11 implements a step of smoothing the location data.

[0089] For example, in the context of the moving average method, at the current instant, the moving average r _avg. of the radial distance is given by the following expression:

[0091] with r _; (t ₀ +At) the radial distance determined between the motor vehicle 10 and the other user i concerned determined at the current time t ₀ +At, r _avg. (t ₀ ) the moving average determined at the previous time (here t ₀ ), r _{avg i} (to+At) the moving average determined at the current time and has the smoothing constant defined previously.

[0092] To detect a possible collision, the computer 11 determines, in step E34, an indicator of the risk of collision based on two location data determined at the two successive times and smoothed (steps E16 and E32).

[0093] In practice, this collision risk indicator is determined by calculating a rate of increase between the two location data determined for the same other user at the two successive times and smoothed.

[0094] At this stage, it can be noted that the identification element makes it possible to guarantee that the location data successively acquired at successive times are indeed associated with the same other user.

[0095] In the case where the location data is represented by means of spherical coordinates, the calculator 11 determines the rate of increase in the radial distance (smoothed) between the motor vehicle 10 and each other user i between time t ₀ (previous instant) and the current instant (t ₀ incremented by a time step At).

[0096] Thus, for another user i, the rate of increase (denoted r is given by the following expression):

[0098] Otherwise formulated, this rate of increase is an instantaneous speed of approaching or moving away from the other user considered.

[0099] Alternatively, the collision risk indicator could be determined directly from the location data determined in steps E14 and E30 (unsmoothed).

[0100] Once the collision risk indicator has been determined, the process continues in step E36. During this step, the computer 11 determines the sign of the collision risk indicator. Interpreting the sign of this collision risk indicator makes it possible to understand the relative movement of the motor vehicle 10 in relation to the other user i concerned.

[0101] More precisely, a negative sign of the collision risk indicator means that the motor vehicle 10 and the other user i concerned are approaching, while a positive sign of this indicator means that the motor vehicle 10 and the other user i concerned move away. [0102] If the collision risk indicator is positive, the process continues in step E38. In this case, as the motor vehicle 10 and the other user i move away, the computer 11 estimates that the risk of collision (with this other user i) is zero. In this eventuality, in step E38, the computer 11 controls the display, for example on the screen present in the passenger compartment of the motor vehicle 10, of the location of the other user i concerned for information purposes. Alternatively, the computer 11 may not transmit any information on this subject to the attention of the driver.

[0103] For example, for the situation illustrated in [Fig.2], we could consider that the motor vehicle 70 is moving away from the intersection 200 and therefore from the motor vehicle 10. In this case, the risk of collision is zero and the driver of the motor vehicle 10 is for example not informed of the presence of this other motor vehicle 70.

[0104] As shown in [Fig.3], the process then continues in step E50 during which the time variable is incremented by a time step to execute the process at the next instant. The process then continues in step E16 with, as current instant, the previous current instant incremented by an additional time step.

[0105] In the case where, in step E36, the collision risk indicator has been indicated as negative, the process continues in step E40. During this step, the radial distance (smoothed), at the current instant, between the motor vehicle 10 and the other user i concerned is compared to a predetermined distance threshold. This predetermined distance threshold makes it possible to set a distance limit below which it is probable that a collision will occur between the motor vehicle 10 and the other user i concerned. This predetermined distance threshold is for example less than 15 meters.

[0106] Advantageously here, and as shown in [Fig.2], it is possible to define three zones Z _b Z ₂ , Z ₃ of collision risk. Each of these zones Z i, Z ₂ , Z ₃ is defined as a circle of origin O and radius d _h d ₂ , d ₃ respectively.

[0107] Each of these zones Z _b Z ₂ , Z ₃ characterizes a different collision risk. For example, zone Zi with radius di corresponds to a high collision risk, zone Z ₂ with radius d ₂ corresponds to a medium collision risk and zone Z ₃ with radius d ₃ corresponds to a low collision risk.

[0108] In the context of the present invention, the radius di is for example equal to 5 meters, the radius d ₂ is for example equal to 10 meters and the radius d ₃ is for example equal to 15 meters.

[0109] In other words, in step E40 (knowing that the collision risk indicator is negative, therefore that the motor vehicle 10 and the other user i are getting closer), the calculator 11 compares the radial distance (smoothed) at rays dd ₂ , d ₃ .

[0110] If the radial distance (smoothed) is less than the radius d _b this means that, in addition to coming closer, the motor vehicle 10 and the other user i are already very close. The risk of collision is very high here. In the case of the situation shown in [Fig.2], the bus 20 could be in this situation if the motor vehicle 10 continues to move forward while the bus 20 is stopped.

[0111] The process continues here in step E42. The computer 11 generates an alert regarding the imminence of a collision with another user i in his environment. This alert is here audible (via the vehicle speakers), haptic (via steering wheel vibrations) or visual (via the display screen).

[0112] The sound alert can for example correspond to a signal whose sound frequency is high (such as that emitted by a reversing radar when there is a very short distance between the vehicle and the detected obstacle). In this case, the computer 11 can also generate a command for an emergency braking system to avoid the collision or, if this is no longer possible, limit the damage of such a collision.

[0113] If the radial distance (smoothed) is between the radius di and the radius d ₂ , this means the motor vehicle 10 and the other user i are approaching each other while being at an average distance from each other. The risk of collision is average here (and implementation of the process at subsequent times will make it possible to monitor the evolution of this risk of collision).

[0114] In the case of the situation represented in [Fig.2], a collision of this type could occur with the cyclist 60 hidden by the bus 20, if the motor vehicle 10 continues to advance.

[0115] In this case, the process continues in step E44. The computer 11 generates, for example, an information alert to draw the driver's attention to the presence of the other user i to whom he is approaching. This alert is here audible (via the vehicle speakers), haptic (via steering wheel vibrations) or visual (via the display screen).

[0116] If the radial distance (smoothed) is between radius d ₂ and radius d ₃ , this means the motor vehicle 10 and the other user i are approaching each other while being at a reasonable distance from each other . The risk of collision is low here (and implementation of the process at subsequent times will make it possible to monitor the evolution of this risk of collision).

[0117] In this case, the process continues in step E46. The computer 11 generates, for example, an information alert to draw the driver's attention to the presence of the other user i to whom he is approaching. This alert is here audible (via the vehicle speakers), haptic (via steering wheel vibrations) or visual (via the display screen).

[0118] Finally, if the radial distance (smoothed) is greater than the radius d ₃ , the motor vehicle 10 and the other user i are relatively far apart (although they are getting closer). In this case, the risk of collision is zero. This case then joins that described previously in which the motor vehicle 10 and the other user i move away. The process then continues in step E38 described previously.

[0119] As shown in [Fig.3], whatever the case, the process then continues in step E50 during which the temporal variable is incremented by a time step to execute the proceeded at the next moment. The process then continues in step El 6 with, as, current instant, the previous current instant incremented by an additional time step.

[0120] Thus, at each of the successive implementations of the different steps, it is always the location data determined at two successive times which are used and analyzed. Consequently, this allows continuous temporal monitoring of the locations of other road users in relation to the motor vehicle 10 and therefore continuous temporal monitoring of possible risks of collision involving the motor vehicle 10.

[0121] Furthermore, this temporal monitoring of the location data of other users can be used to conduct a precise estimation of the trajectories observed by the other users to then be used in the context of driving assistance systems (such as the ADAS system).

[0122] The collision detection method in accordance with the present invention makes it possible to assess the risk of a possible collision between the motor vehicle 10 and at least one other user, whether this other user is positioned, relative to the motor vehicle 10. , forward, backward, sideways, whether there are one or more other users involved, or even whether certain users are hidden (like the cyclist 60 in [Fig.2]).

[0123] The present invention also relates to a method for calibrating a collision detection system between the motor vehicle 10 and another user 20, 30, 40, 50, 60, 70 of the road. This calibration process aims to take advantage of the advantages of the collision detection process described above in order to calibrate (and therefore make more efficient) a “classic” collision detection system which is usually fitted to motor vehicles.

[0124] This calibration process, represented in the form of a flowchart ([Fig.4]), comprises a succession of steps.

[0125] As shown in [Fig.4], this calibration process begins at step E100 during which the remote sensing and/or imaging sensors of the detection system 15 acquire data concerning the environment of the motor vehicle 10.

[0126] In step E102, the control unit 17 of the collision detection system 15 analyzes the acquired data to deduce first location data of the other users 20, 30, 40, 50, 60, 70 present in the environment of the motor vehicle 10. This determination of the location data is implemented taking into account the processing parameters configuring the control unit 17. These processing parameters were for example initially determined during the manufacture of the motor vehicle 10 and the installation of the collision detection system 15 in the motor vehicle 10 This step E102 being well known elsewhere, it will not be described here in detail.

[0127] The method continues in step E104 during which the computer 11 determines second location data for other users by implementing the collision detection method described previously (and shown in [Fig.3]) .

[0128] The computer 11 then compares, in step E106, the first location data determined by the detection system 15 and the second location data obtained by implementing the collision detection method. For example, the calculator 11 determines the difference between the location data determined by the detection system 15 and those obtained by implementing the collision detection method.

[0129] In step E108, this difference is compared to a predetermined threshold. If the difference is less than the predetermined threshold, it is considered that the detection system 15 is suitably calibrated. Here, this predetermined threshold is for example of the order of 5%. The process therefore resumes at step E100.

[0130] On the other hand, if the difference is greater than this predetermined threshold, this means that the difference between the location data determined by the detection system 15 and those obtained by the implementation of the collision detection method is significant. . In other words, this means that the detection system 15 was not able to detect all the other users present in the environment of the motor vehicle 10. In particular, this indicates that the detection system 15 does not was not initially configured to successfully identify all the other users present in the environment of the motor vehicle 10.

[0131] In this case, the process continues in step El 10. During this step, the computer 11 transmits instructions for updating the parameters of the control unit 17 so as to improve the detection performance of the detection system 15.

[0132] This calibration process is preferably implemented in the testing phase of the motor vehicle 10. Alternatively, it can also be implemented during the movement of the motor vehicle 10. Artificial intelligence could be used for this. regard, so as to make it possible to improve the detection performance of the detection system 15 even when the weather conditions are degraded.

Claims

[Claim 1] Method for detecting an upcoming collision between a motor vehicle (10) and at least one other user (20, 30, 40, 50, 60, 70) present in the environment of the motor vehicle (10), the motor vehicle (10) comprising a computer (11) equipped with a communication unit (11A) and the other user (20, 30, 40, 50, 60, 70) comprising a mobile terminal (21, 22, 23 , 24, 25, 26, 31, 41, 51, 61, 71) configured to communicate with the communication unit (1 IA) of the computer (11), the method comprising, at two successive times, steps of:

- detection of the presence of the other user (20, 30, 40, 50, 60, 70) in the environment of the motor vehicle (10) by transmission, by the communication unit (11A) of the computer (11) , a wireless communication signal,

- reception, by the communication unit (1 IA) of the computer (11), of a response signal transmitted by the other user (20, 30, 40, 50, 60, 70) following reception of the signal wireless communication,

- determination of location data of the other user (20, 30, 40, 50, 60, 70) by means of characteristics of the response signal, and

- detection of an upcoming collision between said motor vehicle (10) and the other user (20, 30, 40, 50, 60, 70) by determining a collision risk indicator based on the location data determined at both successive moments.

[Claim 2] Method according to claim 1, in which the collision risk indicator is determined by calculating a rate of increase between the location data determined at the two successive times.

[Claim 3] Method according to claim 1 or 2, in which, each determined location data comprising a relative distance between the motor vehicle (10) and the other user (20, 30, 40, 50, 60, 70), in the collision detection step, sub-steps of:

- determination of a sign of the collision risk indicator, and

- comparison of at least one of the relative distances determined with a predetermined distance threshold, an upcoming collision being detected when the collision risk indicator is negative and said relative distance is less than said predetermined distance threshold.

[Claim 4] Method according to claim 3, in which the distance threshold predetermines completed is less than 15 meters.

[Claim 5] Method according to any one of claims 1 to 4, in which, at each successive moment, there is provided a step of identifying the other user (20, 30, 40, 50, 60, 70) by an identification element transmitted in said response signal.

[Claim 6] Method according to claim 5, in which steps are provided for:

- encryption of said identification element, and

- storage of said encrypted identification element in a memory of said computer (11).

[Claim 7] Method according to any one of claims 1 to 6, in which, before determining the collision risk indicator, a step of smoothing the location data is provided, preferably by determining an average exponential mobile.

[Claim 8] Method according to any one of claims 1 to 7, in which the wireless communication is established according to the Bluetooth® standard or according to the Ultra Wide Band modulation technique.

[Claim 9] Method for calibrating a collision detection system (15) between a motor vehicle (10) and at least one other user (20, 30, 40, 50, 60, 70) present in the environment of the motor vehicle (10), said detection system (15) comprising at least one remote sensing and/or imaging sensor and a control unit (17), the motor vehicle (10) comprising a computer (11) provided with a communication unit (11 A), the method comprising steps of:

- acquisition, by the remote sensing and/or imaging sensor, of data concerning the environment of the motor vehicle (10),

- determination of location data for the other user (20, 30, 40, 50, 60, 70) based on the acquired data and taking into account processing parameters of the control unit (17) of the system detection (15),

- obtaining the location data of said other user (20, 30, 40, 50, 60, 70) by implementing the method according to any one of claims 1 to 8,

- updating of processing parameters of the control unit (17).

[Claim 10] Motor vehicle (10) comprising a computer (11) provided with a communication unit (1 IA) and configured to implement the detection method according to one of claims 1 to 8.