Method for detecting an impending collision, method for calibrating a collision detection system, and associated motor vehicle

Abstract

The invention relates to a method for detecting an impending collision between a motor vehicle (10) and at least one other user (20, 30, 40, 50, 60, 70) present in the vicinity 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, at two successive instants, the steps of: - detecting the presence of the other user in the vicinity of the motor vehicle by emission, by the communication unit of the computer, of a wireless communication signal, - reception, by the communication unit of the computer, of a response signal emitted by the other user following the reception of the wireless communication signal,- Determination of the other user's location data using characteristics of the response signal, and - detection of an impending collision between said motor vehicle and the other user by determining a collision risk indicator based on the location data determined at two successive times. Figure for the abstract: Fig. 2,

Description

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

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

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

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

[0004] The invention also relates to an associated motor vehicle. State of the art

[0005] In order to improve the safety of motor vehicles, they are currently being equipped with driver assistance systems (or AD AS for "Advanced driver-as-assistance Systems" according to the commonly used Anglo-Saxon acronym) or even highly automated driving systems.

[0006] Among these systems, we know in particular the automatic emergency braking systems (better known by the abbreviation AEB, from the 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] Automatic avoidance systems (better known by the abbreviation AES, from the English "Automatic Evasive Steering" or "Automatic Emergency Steering") are also known, which allow the obstacle to be avoided by diverting the vehicle from its trajectory, by acting on the direction of the vehicle.

[0008] These systems generally allow the detection of an imminent collision with another motor vehicle, the alerting of the driver and, if necessary, the activation of the braking system until the motor vehicle comes to a complete stop.

[0009] To enable this detection, these systems generally include sensors equipped with radar 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, inside the vehicle's passenger compartment. tomobile. The analysis of 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 various sensors used have disadvantages, particularly in the event of adverse weather conditions, for example in foggy or rainy weather.

[0011] Indeed, water droplets in the air during foggy or rainy weather scatter or deflect the laser beam emitted by a lidar, making it difficult to analyze the reflected beams for detecting objects in the vicinity of the motor vehicle. Similarly, water droplets on a windshield can obscure all or part of the field of vision of a data acquisition sensor located inside the vehicle. Under these conditions, detecting other road users in the vicinity of the motor vehicle is therefore difficult, if not impossible.

[0012] Furthermore, in the event of malfunction and / or unavailability of the detection system in the motor vehicle, the driver can only rely on his vigilance (and 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, regardless of weather conditions or in the event of malfunction or unavailability of detection systems in the motor vehicle.

[0014] More specifically, the invention proposes a method for detecting an impending collision between a motor vehicle and at least one other user present in the vicinity 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, the steps of: - detection of the presence of the other user in the environment of the motor vehicle by emission, by the computer's communication unit, of a wireless communication signal, - reception, by the computer's communication unit, of a response signal emitted by the other user following the reception of the wireless communication signal,

[0015] - determination of a location data of the other user by means of characteristics teristics of the response signal, and - detection of an impending collision between said motor vehicle and the other vehicle lizer by determining a collision risk indicator based on location data determined at two successive times.

[0016] Thus, according to the present invention, the detection of a potential collision is achieved by using wireless communications that can be established between the vehicle's computer and other road users. This method is particularly simple to implement because it relies on establishing wireless communications with mobile terminals commonly used today.

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

[0018] Other advantageous and non-limiting features 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 two successive times; - each determined location data point including a relative distance between the motor vehicle and the other user, the collision detection stage includes sub-steps of: a) determining a sign for the collision risk indicator, and b) comparison of at least one of the determined relative distances with a predetermined distance threshold, an imminent collision is detected when the collision risk indicator is negative and said relative distance is less than said predetermined distance threshold; - the predetermined distance threshold is less than 15 meters; - at each successive instant, there is a planned step of identifying the other user by an identification element transmitted in said response signal; - The planned steps include:

[0019] al) encryption of said identification element, and bl) storing said encrypted identification element in a memory of said computer; - before determining the collision risk indicator, a step of smoothing the location data is planned; - the location data smoothing step is carried out by determining an exponential moving average; - Wireless communication is established according to the Bluetooth® standard; and - Wireless communication is established using Ultra Wideband modulation technology.

[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 vicinity of the motor vehicle, said detection system comprising at least one remote sensing and / or imaging sensor and a control unit, the motor vehicle comprising a computer equipped with a communication unit, the method comprising the steps of: - Acquisition, by the remote sensing and / or imaging sensor, of data concerning the environment of the motor vehicle, - Determining the location data of the other user based on the acquired data and taking into account the processing parameters of the detection system's control unit, - obtaining the location data of said other user by implementing the detection process described above, - determining the difference between the determined location data and the obtained location data, then if said difference exceeds a predetermined threshold, - updating the processing parameters of the control unit

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

[0022] Of course, the various features, variants, and embodiments of the invention can be combined with one another in various ways, provided they are not incompatible or mutually exclusive. Detailed description of the invention

[0023] The following description with regard to the attached drawings, given by way of non-limiting examples, will make it clear what the invention consists of and how it can be carried out.

[0024] On the attached drawings:

[0025] [Fig-1] represents a schematic top view of a motor vehicle adapted to implement a process in accordance with 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 the form of a flowchart, an example of a method for detecting a collision between the motor vehicle and another road user conforming to the invention; and

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

[0029] In [Fig. 1], a motor vehicle 10 adapted to implement the invention is shown.

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

[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.

[0032] This vehicle 10 comprises a powertrain, a braking system, and a steering system for turning the vehicle (not shown in the figure). Typically, the steering system comprises an electronically controlled power steering actuator, the powertrain comprises an electronically controlled engine control actuator, and the braking system comprises an electronically controlled brake actuator.

[0033] The vehicle 10 also includes an electronic and / or computer processing unit (hereinafter referred to as 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 come from sensors or third-party computers.

[0035] For example, among these sensors, the following are provided: - a device such as a front camera and / or a side camera, enabling the position of the motor vehicle 10 to be determined in relation to its lane of travel, and - a device such as a RADAR remote detector and / or a LIDAR remote detector, enabling the detection of 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 (through which the motor vehicle 10 can move in traffic autonomously, without intervention from the driver).

[0039] Thanks to its memory, the calculator 11 stores a computer application, consisting of computer programs comprising instructions whose execution by the computer enables the implementation of the tracking process described below.

[0040] Finally, in the context of the present invention, the computer 11 includes 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 phone (or “smartphone” according to the commonly used Anglo-Saxon term).

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

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

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

[0045] Alternatively, the wireless communication may 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, the motor vehicle 10 is considered to be travelling on a traffic lane 100A. In [Fig.2], the motor vehicle 10 is shown travelling 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 road users 20, 30, 40, 50, 60, 70 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 bus 20, for example, several people are considered to be each equipped with a mobile terminal 21, 22, 23, 24, 25, 26.

[0050] The present invention relates to a method for detecting an imminent collision between The motor vehicle 10 and one or more of the other road users 20, 30, 40, 50, 60, 70. This method aims to enable the detection of a possible future collision (upstream, before it occurs) based on wireless communications established between the motor vehicle 10 and at least one other road user 20, 30, 40, 50, 60, 70.

[0051] More specifically, 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 road users 20, 30, 40, 50, 60, 70, the method according to the invention makes it possible at any given moment to locate each of the other road users 20, 30, 40, 50, 60, 70 (simultaneously). Then, by tracking the relative movement of each of the other road users 20, 30, 40, 50, 60, 70 with respect to the motor vehicle 10, the method makes it possible to assess the risk of a future collision for the motor vehicle 10.

[0052] For this purpose, 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 start and stop of the motor vehicle 10.

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

[0054] As shown in [Fig. 3], the process begins at step E2, which initializes a time variable t. This time variable t corresponds to the start time of the process implementation. For example, here, this time variable t is initialized at time t0. We will consider this time t0 to be a time distinct from the moment when vehicle 10 is started.

[0055] The process then continues in step E4. During this step, the communication unit 11A 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 emitting this plurality of wireless communication signals. This plurality of wireless communication signals is intended 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 communication signal emitted by the communication unit 11 A, emits, in response, a wireless response communication signal (step E4).

[0057] At step E6, this wireless communication response signal is received by the unit of communication 1 AI 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 (who have issued a response to the wireless communication signal).

[0058] It may be noted here that the motor vehicle 10 may also include mobile terminals (not shown) which could potentially receive the communication signal emitted by the computer 11 and transmit 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 specifically, in step E8, the computer 11 identifies each other user 20, 30, 40, 50, 60, 70 by means of the wireless response communication signal which includes an identification element associated with the other user 20, 30, 40, 50, 60, 70 concerned.

[0060] Indeed, within the framework 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 a UUID for "Universal Unique Identifier"). The computer 11 receives this identification element associated with each other user 20, 30, 40, 50, 60, 70 upon receiving the reply wireless communication signal.

[0061] This identification element allows the calculator 11 to follow the other user 20, 30, 40, 50, 60, 70 concerned at all times.

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

[0063] The encryption of the identification element is, for example, implemented by applying 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").

[0064] The encrypted identification element is then stored in the memory of the computer 11 (step E12).

[0065] The process continues in step E14. During this step, the computer 11 determines a 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 wireless communication signal received by the computer 11 for each other user 20, 30, 40, 50, 60, 70.

[0066] For example, in the context of a 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 the angles of arrival ("Angle of Arrival") 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 frame of reference of the motor vehicle 10.

[0068] In general, as shown in [Fig.1], an orthonormal vehicle frame (in Cartesian coordinates) is defined with respect to the motor vehicle 10, characterized by an origin O located for example in the middle of the front axle, a longitudinal axis X oriented from the front to the rear of the vehicle, a lateral axis Y, and a vertical axis Z oriented upwards (the vehicle being considered horizontal).

[0069] The spherical coordinates are then defined, with respect to this orthonormal frame with (for each other user i among the other users 20, 30, 40, 50, 60, 70): r; 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 plane of the road, 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 small and does not characterize the location of the other users 20, 30, 40, 50, 60, 70 very much.

[0071] These spherical coordinates are a function of time. Thus, at time t0, at step E14, for each other user, the computer 11 determines the spherical coordinates of each other user i with respect 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 t0, 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 computer 11 deduces the relative positioning (front, rear, right, left) of each other user 20, 30, 40, 50, 60, 70 with respect to the motor vehicle 10.

[0074] In step E16, the computer 11 implements a smoothing step for the location data. This smoothing step has the advantage of eliminating point discrepancies or minimizing noise from the raw determination of the location data.

[0075] This smoothing step corresponds, for example, to a 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] Within the framework of this method, the moving average rmoyJ of the radial distance is given by the following expression:

[0078] [Math.l] rmOyt (r0) = ar^ + (1 - a)rmoyl{t0 - A r)

[0079] with r;(t0) the radial distance determined between the motor vehicle 10 and the other user i concerned determined at the current time t0, rmoy i(t0-At) the moving average determined at the previous time, rmoy i(t0) the moving average determined at the current time and a a smoothing constant defined by the following expression:

[0080] [Math.2] (Z — u ïV+1

[0081] with N an integer to be chosen according to the desired smoothing accuracy.

[0082] It should be noted that the moving average rmoy i(to-At) at the very first instant of implementation of the process 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 at step El8, during which the time variable t is incremented by a predetermined time step. The instant at which the following steps are implemented (after incrementing) is referred to hereafter as the "current instant".

[0084] Steps E20 to E32 are respectively the same as steps E4 to E18 described previously. They aim to enable 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 above, the calculator 11 determines another location data associated with each other user 20, 30, 40, 50, 60, 70 and corresponding to his 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 points determined at two successive times. These two location data points determined at two successive times will make it possible to assess the possibility of a collision occurring between the motor vehicle 10 and at least one of the other road users 20, 30, 40, 50, 60, 70.

[0088] Similar to step E16 described above, 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 time, the moving average rmoyJ of the radial distance is given by the following expression:

[0090] [Math.3] Tmoy. ( + A t ) = (Zr,^?Q + A + (1 - Cl}FmOy£tQ)

[0091] with r^to+At) the determined radial distance between the motor vehicle 10 and the other user i concerned determined at the current time t0+At, rmoy i(t0) the moving average determined at the previous time (here t0), rmoy i(to+At) the moving average determined at the current time and a the smoothing constant defined previously.

[0092] To detect a possible collision, the computer 11 determines, at step E34, a collision risk indicator based on two location data determined at two successive instants 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 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 are represented by means of spherical coordinates, the computer 11 determines the rate of increase of the radial distance (smoothed) between the motor vehicle 10 and each other user i between time t0 (previous time) and current time (to incremented by a time step At).

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

[0097] [Math.4] _ r^yj^+te)my j(fo) T ~ Xt

[0098] In other words, 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 to step E36. In this step, the control unit 11 determines the sign of the collision risk indicator. Interpreting the sign of this collision risk indicator makes it possible to understand the relative displacement of the motor vehicle 10 with respect to the other user i involved.

[0101] More specifically, a negative sign of the collision risk indicator means that the motor vehicle 10 and the other user i concerned are getting closer, while a positive sign of this indicator means that the motor vehicle 10 and the other user i concerned are moving away.

[0102] If the collision risk indicator is positive, the process continues at step E38. In this case, as the motor vehicle 10 and the other user i move away, the control unit 11 considers the risk of collision (with this other user i) to be zero. In this event, at step E38, the control unit 11 commands the display, for example on the screen in the passenger compartment of the motor vehicle 10, of the location of the other user i for informational purposes. Alternatively, the control unit 11 may not provide any information on this subject to the driver.

[0103] For example, for the situation illustrated in [Fig.2], one 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 not, for example, informed of the presence of this other motor vehicle 70.

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

[0105] If, in step E36, the collision risk indicator was indicated as negative, the process continues in step E40. In this step, the current radial (smoothed) distance between the motor vehicle 10 and the other user i is compared to a predetermined distance threshold. This predetermined distance threshold establishes a distance limit below which a collision between the motor vehicle 10 and the other user i is likely. This predetermined distance threshold is, for example, less than 15 meters.

[0106] Advantageously, as shown in [Fig. 2], it is possible to define three collision risk zones Zb, Z2, Z3. Each of these zones Zb, Z2, Z3 is defined as a circle with origin O and respective radii db, d2, d3.

[0107] Each of these zones Zb, Z2, Z3 characterizes a different collision risk. For example, zone Zi with radius di corresponds to a high collision risk, zone Z2 with radius d2 corresponds to a medium collision risk, and zone Z3 with radius d3 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 d2 is for example equal to 10 meters and the radius d3 is for example equal to 15 meters.

[0109] In other words, at step E40 (knowing that the collision risk indicator is negative, therefore that the motor vehicle 10 and the other user i are approaching each other), the computer 11 compares the radial (smoothed) distance to the radii db d2, d3.

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

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

[0112] The audible alert may, for example, correspond to a signal with a high sound frequency (such as that emitted by a reversing radar when the vehicle is very close to the detected obstacle). In this case, the control unit 11 may also generate a command for an emergency braking system to avoid the collision or, if this is no longer possible, to limit the damage from such a collision.

[0113] If the radial (smoothed) distance is between radius di and radius d2, this means that the motor vehicle 10 and the other user i are approaching each other while remaining at an average distance. The risk of collision is average here (and implementing the method at subsequent times will allow us 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 move forward.

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

[0116] If the radial (smoothed) distance is between radius d2 and radius d3, this means that the motor vehicle 10 and the other user i are approaching each other while remaining at a reasonable distance. The risk of collision is low here (and implementing the method at subsequent times will allow us to monitor the evolution of this collision risk).

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

[0118] Finally, if the (smoothed) radial distance is greater than the radius d3, 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 corresponds to the one described previously. in which the motor vehicle 10 and the other user i move away. The process then continues at step E38 described previously.

[0119] As shown in [Fig. 3], in all cases, the process then proceeds to step E50, where the time variable is incremented by one time step to execute the process at the next instant. The process then proceeds to step E16, with the current instant being the previous current instant incremented by one additional time step.

[0120] Thus, at each successive implementation of the different steps, the location data determined at two successive times are always used and analyzed. Consequently, this allows for continuous temporal monitoring of the locations of other road users relative to the motor vehicle 10, and therefore continuous temporal monitoring of potential collision risks involving the motor vehicle 10.

[0121] In addition, this temporal tracking of the location data of other users can be used to conduct an accurate estimation of the trajectories observed by other users for subsequent use in driver assistance systems (such as the AD AS system).

[0122] The collision detection method according to 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, in relation to the motor vehicle 10, in front, behind, on the side, whether there is one or more other users involved, or even whether some 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 road user 20, 30, 40, 50, 60, 70. This calibration method aims to take advantage of the benefits of the collision detection method described above in order to calibrate (and thus improve the performance of) a "conventional" collision detection system 15 commonly 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 sensing system 15 acquire data concerning the environment of the motor vehicle 10.

[0126] At step E102, the control unit 17 of the collision detection system 15 analyzes the acquired data to deduce initial location data for the other users 20, 30, 40, 50, 60, 70 present in the vicinity of the motor vehicle 10. This determination of 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 in detail here.

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

[0128] The control unit 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 control unit 11 determines the difference between the location data determined by the detection system 15 and that obtained by implementing the collision detection method.

[0129] At step E108, this difference is compared to a predetermined threshold. If the difference is less than the predetermined threshold, the detection system 15 is considered to be properly calibrated. Here, this predetermined threshold is, for example, on the order of 5%. The process then resumes at step E100.

[0130] Conversely, if the difference exceeds this predetermined threshold, it means that the discrepancy between the location data determined by the detection system 15 and those obtained by implementing the collision detection method is significant. In other words, it means that the detection system 15 was unable to detect all other users present in the vicinity of the motor vehicle 10. In particular, it indicates that the detection system 15 was not initially configured to successfully identify all other users present in the vicinity of the motor vehicle 10.

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

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

Claims

Claims

1. Method for detecting an imminent 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: - detecting 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), of 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 wireless communication signal, - determining location data of the other user (20, 30, 40, 50, 60, 70) by means of characteristics of the response signal, said characteristics comprising at least a power and an angle of arrival of the response signal, and - detecting an upcoming collision between said motor vehicle (10) and the other user (20, 30, 40, 50, 60, 70) by determining a collision risk indicator depending on the location data determined at the two successive times.,

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

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 are provided for: - determining a sign of the collision risk indicator, a negative sign meaning that the motor vehicle (10) and the other user (20, 30, 40, 50, 60, 70) are getting closer, while a positive sign means that the motor vehicle (10) and the other user (20, 30, 40, 50, 60, 70) are moving away, and - comparison of at least one of the determined relative distances with a predetermined distance threshold, an imminent collision being detected when the collision risk indicator is negative and said relative distance is less than said predetermined distance threshold.

4. The method of claim 3, wherein the predetermined distance threshold is less than 15 meters.

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

6. Method according to claim 5, in which steps are provided of: - encrypting said identification element, and - storing said encrypted identification element in a memory of said computer (11).

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 exponential moving average.

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

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: - acquiring, by the remote sensing and / or imaging sensor, data relating to the environment of the motor vehicle (10), - determining location data of the other user (20, 30, 40, 50, 60, 70) as a function of the acquired data and taking into account processing parameters of the control unit (17) of the detection system (15), - obtaining of 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, - determination of a difference between the determined location data and the obtained location data, then if the said difference is greater than a predetermined threshold, - updating of processing parameters of the control unit (17).

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.

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