A occupant protection system and control method based on human body injury potential field

Abstract

The present invention discloses an occupant protection system and control method based on human body injury potential field, including an occupant protection warning module, which includes GPS, a vehicle speed meter, a laser radar, a first warning unit, a static obstacle collision risk potential field calculation unit, a dynamic obstacle risk potential field calculation unit and a second warning unit; the occupant protection path planning module includes a virtual time domain human body injury prediction unit, a human body injury potential field calculation unit and a discrete path point prediction unit; the occupant protection control module includes a path fitting unit and an MPC controller. The present invention is based on human body injury prediction, and when a vehicle is about to have an unavoidable collision, it adaptively plans a protection route with minimal damage, thereby maximizing the protection of occupant safety in traffic accidents; thereby effectively reducing occupant casualties in traffic accidents; it is applicable to a variety of complex road traffic scenes, and has the advantages of simple structure and strong robustness.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile safety, and in particular to an occupant protection system and a control method based on a human body injury potential field. Background Art

[0002] Occupant protection systems are divided into two forms: passive safety and active safety. Traditional passive safety devices often provide passive protection after the occupants are injured, which can easily cause secondary injuries to the occupants. With the development of intelligent driving, active safety devices are gradually configured in unmanned vehicles. However, current active safety devices have poor timeliness and lack consideration for the injuries of the occupants, making it difficult to provide the best protection for the occupants based on road conditions. Summary of the invention

[0003] The purpose of the present invention is to provide an occupant protection system and control method based on human body injury potential field. Based on human body injury prediction, when a vehicle is about to have an inevitable collision, a protection route with minimal damage is adaptively planned, thereby maximizing the protection of occupant safety in traffic accidents.

[0004] According to one object of the present invention, the present invention provides an occupant protection system based on a human body injury potential field, comprising:

[0005] The occupant protection warning module is used to sense the driving environment and form a warning signal. The occupant protection warning module includes GPS, a speedometer, a laser radar, a first warning unit, a static obstacle collision risk potential field calculation unit, a dynamic obstacle risk potential field calculation unit and a second warning unit;

[0006] An occupant protection planning module is used to plan a collision avoidance route with minimal human damage when the vehicle is about to have an unavoidable collision. The occupant protection path planning module includes a virtual time domain human damage prediction unit, a human damage potential field calculation unit, and a discrete path point prediction unit;

[0007] The occupant protection control module is used to control the vehicle to track the predicted collision avoidance trajectory, and the occupant protection control module includes a path fitting unit and an MPC controller.

[0008] The above-mentioned control method of the occupant protection system based on the human body injury potential field comprises the following steps:

[0009] Step 1: Obtain the spatial position (X, Y) of the vehicle through GPS and obtain the speed of the bicycle (V I_X , V I_Y ), and direction of travel;

[0010] Step 2, obtaining the relative position and relative speed of objects around the vehicle through the laser radar, and inputting the position signal and speed signal into the first warning unit;

[0011] Step 3: The first warning unit determines whether the vehicle has a collision risk by calculating the safe vehicle distance. If the distance is less than the safe vehicle distance, the first warning signal is output;

[0012] Step 4: determine an object that is smaller than the safe vehicle distance as an obstacle, and judge the obstacle to be a static obstacle or a dynamic obstacle based on the relative position change of the obstacle;

[0013] Step 5: If it is a static obstacle, the first warning signal is input into the static obstacle collision risk potential field calculation unit, and the static obstacle spatial position (X s , Y s ) and static obstacle potential field coefficient μ S_C , calculate the static obstacle collision risk potential field E according to the following formula: S_C ;

[0014]

[0015] Step 6: If it is a dynamic obstacle, the first warning signal is input into the dynamic obstacle collision risk potential field calculation unit, and the static obstacle spatial position (X D , Y D ), dynamic obstacle potential field coefficient μ D_C , relative speed V R and the relative motion vector angle θ I , calculate the static obstacle collision risk potential field E according to the following formula: S_C ;

[0016]

[0017] Step 7: Substitute the vehicle position and speed into the static obstacle collision risk potential field and the dynamic obstacle risk potential field to determine whether it is within the dangerous potential field range. If it is within the safety threshold, end the occupant protection warning;

[0018] Step 8: If it is within the dangerous potential field range, the second warning unit outputs a second warning signal;

[0019] Step 9, after receiving the second warning signal, the virtual time-domain human injury prediction unit constructs a human injury prediction model according to the human injury database, wherein the human injury prediction model takes vehicle speed, collision angle, and collision position as inputs, and outputs the AIS levels of human head, chest, and leg injuries;

[0020] Step 10, calculating the vehicle speed, collision angle, and collision position when the self-vehicle collides with the obstacle vehicle in the current vehicle state according to the static obstacle collision risk potential field and the dynamic obstacle risk potential field, and predicting the AIS level of human head, chest, and leg injuries in the current vehicle state through the human injury prediction model;

[0021] Step 11, determine whether it is higher than a predetermined threshold value, if it is lower, emergency braking is performed, if it is higher, the human body injury potential field calculation unit takes the obstacle as the center, establishes the human head, chest, and leg injury potential energy cloud, and the human head, chest, and leg injury potential energy cloud is constructed according to the following formula, and is related to the relative vehicle speed V R 、Velocity vector angle θ I and AIS level were positively correlated;

[0022] J Head =f(V R ,θ I , AIS Head )

[0023] J chest =f(V R ,θ I , AIS chest )

[0024] J leg =f(V R ,θ I , AIS leg )

[0025] Step 12, superimpose the human head, chest, and leg injury potential energy clouds established respectively and assign correction factors in turn, wherein the correction factors are empirical coefficients, and the correction factors corresponding to the head, chest, and leg injury potential energy clouds are reduced in turn to establish the human body injury potential field J Human ;

[0026] J Human =μ1J Head +μ2J chest +μ3J leg

[0027] Step 13, the discrete path point prediction unit establishes a road coordinate system, takes the current centroid position of the vehicle as the starting path point, and the centroid position of the obstacle as the ending path point, discretizes the potential field range between the vehicle and the obstacle into a number of path points, and selects the path point with lower potential energy according to the established human body injury potential field;

[0028] Step 14, the path fitting unit uses a polynomial to fit the path points with lower potential energy into the desired path;

[0029] Step 15, controlling the wheel steering angle through the MPC controller to move along the desired path until reaching the end path point.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The occupant protection system of the present invention is based on the human body injury potential field. It is based on the prediction of human body injuries. When a vehicle is about to have an inevitable collision, it adaptively plans a protection route with the least damage, thereby maximizing the protection of occupant safety in traffic accidents. The construction of the human body injury potential field includes the more important head, chest and leg injuries in human body injuries, and the potential field is corrected according to the lethality of injuries in different parts of the head, thereby effectively reducing occupant casualties in traffic accidents. It is suitable for a variety of complex road traffic scenes and has the advantages of simple structure and strong robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 The following is a flowchart of an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] The components of the present invention are all universal standard components or components known to those skilled in the art, and their structures and principles can be known to those skilled in the art through technical manuals or conventional experimental methods.

[0035] Example 1

[0036] like Figure 1 As shown:

[0037] An occupant protection system based on a human body injury potential field, comprising:

[0038] The occupant protection warning module is used to sense the driving environment and form a warning signal. The occupant protection warning module includes GPS, a speedometer, a laser radar, a first warning unit, a static obstacle collision risk potential field calculation unit, a dynamic obstacle risk potential field calculation unit and a second warning unit;

[0039] An occupant protection planning module is used to plan a collision avoidance route with minimal human damage when the vehicle is about to have an unavoidable collision. The occupant protection path planning module includes a virtual time domain human damage prediction unit, a human damage potential field calculation unit, and a discrete path point prediction unit;

[0040] The occupant protection control module is used to control the vehicle to track the predicted collision avoidance trajectory, and the occupant protection control module includes a path fitting unit and an MPC controller.

[0041] The above-mentioned control method of the occupant protection system based on the human body injury potential field comprises the following steps:

[0042] Step 1: Obtain the spatial position (X, Y) of the vehicle through GPS and obtain the speed of the bicycle (V I_X , V I_Y ), and direction of travel;

[0043] Step 2, obtaining the relative position and relative speed of objects around the vehicle through a laser radar, and inputting the position signal and speed signal into the first warning unit;

[0044] Step 3: The first warning unit determines whether the vehicle has a collision risk by calculating the safe vehicle distance, and outputs a first warning signal if the vehicle is less than the safe vehicle distance.

[0045] Step 4: determine an object that is smaller than the safe vehicle distance as an obstacle, and judge the obstacle to be a static obstacle or a dynamic obstacle based on the relative position change of the obstacle;

[0046] Step 5: If it is a static obstacle, the first warning signal is input into the static obstacle collision risk potential field calculation unit, and the static obstacle spatial position (X s , Y s ) and static obstacle potential field coefficient μ S_C , calculate the static obstacle collision risk potential field E according to the following formula: S_C ;

[0047]

[0048] Step 6: If it is a dynamic obstacle, the first warning signal is input into the dynamic obstacle collision risk potential field calculation unit, and the static obstacle spatial position (X D , Y D ), dynamic obstacle potential field coefficient μ D_C , relative speed V R and the relative motion vector angle θ I , calculate the static obstacle collision risk potential field E according to the following formula: S_C ;

[0049]

[0050] Step 7: Substitute the vehicle position and speed into the static obstacle collision risk potential field and the dynamic obstacle risk potential field to determine whether it is within the dangerous potential field range. If it is within the safety threshold, end the occupant protection warning;

[0051] Step 8: If it is within the dangerous potential field range, the second warning unit outputs a second warning signal;

[0052] Step 9, after receiving the second warning signal, the virtual time-domain human injury prediction unit constructs a human injury prediction model according to the human injury database, wherein the human injury prediction model takes vehicle speed, collision angle, and collision position as inputs, and outputs the AIS levels of human head, chest, and leg injuries;

[0053] Step 10, calculating the vehicle speed, collision angle, and collision position when the self-vehicle collides with the obstacle vehicle in the current vehicle state according to the static obstacle collision risk potential field and the dynamic obstacle risk potential field, and predicting the AIS level of human head, chest, and leg injuries in the current vehicle state through the human injury prediction model;

[0054] Step 11, determine whether it is higher than a predetermined threshold value, if it is lower, emergency braking is performed, if it is higher, the human body injury potential field calculation unit takes the obstacle as the center, establishes the human head, chest, and leg injury potential energy cloud, and the human head, chest, and leg injury potential energy cloud is constructed according to the following formula, and is related to the relative vehicle speed V R 、Velocity vector angle θ I and AIS level were positively correlated;

[0055] J Head =f(V R ,θ I , AIS Head )

[0056] J chest =f(V R ,θ I , AIS chest )

[0057] J leg =f(V R ,θ I , AIS leg )

[0058] Step 12, superimpose the human head, chest, and leg injury potential energy clouds established respectively and assign correction factors in turn, wherein the correction factors are empirical coefficients, and the correction factors corresponding to the head, chest, and leg injury potential energy clouds are reduced in turn to establish the human body injury potential field J Human ;

[0059] J Human =μ1J Head +μ2Jchest +μ3J leg

[0060] Step 13, the discrete path point prediction unit establishes a road coordinate system, takes the current centroid position of the vehicle as the starting path point, and the centroid position of the obstacle as the ending path point, discretizes the potential field range between the vehicle and the obstacle into a number of path points, and selects the path point with lower potential energy according to the established human body injury potential field;

[0061] Step 14, the path fitting unit uses a polynomial to fit the path points with lower potential energy into the desired path;

[0062] Step 15, controlling the wheel steering angle through the MPC controller to move along the desired path until reaching the end path point.

[0063] The occupant protection system based on human body injury potential field proposed by the present invention is based on human body injury prediction. When the vehicle is about to have an inevitable collision, it adaptively plans a protection route with the least damage, thereby maximizing the protection of occupant safety in traffic accidents.

[0064] In the occupant protection system based on the human body injury potential field proposed by the present invention, the construction of the human body injury potential field includes the more important head, chest and leg injuries in human body injuries, and the potential field is modified according to the lethality of injuries at different positions of the human head, thereby effectively reducing the casualties of occupants in traffic accidents;

[0065] The occupant protection system based on the human body injury potential field proposed by the present invention is applicable to a variety of complex road traffic scenes and has the advantages of simple structure and strong robustness.

[0066] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A control method for an occupant protection system based on a human body injury potential field, characterized in that: The steps include: Step 1: Get the spatial position (X, Y) of the vehicle through GPS and the speed of the vehicle through the speedometer , and direction of travel; Step 2, obtaining the relative position and relative speed of objects around the vehicle through a laser radar, and inputting the position signal and speed signal into the first warning unit; Step 3: The first warning unit determines whether the vehicle has a collision risk by calculating the safe vehicle distance, and outputs a first warning signal if the vehicle is less than the safe vehicle distance. Step 4: determine an object that is smaller than the safe vehicle distance as an obstacle, and judge the obstacle to be a static obstacle or a dynamic obstacle based on the relative position change of the obstacle; Step 5: If it is a static obstacle, the first warning signal is input into the static obstacle collision risk potential field calculation unit, and the static obstacle spatial position is calculated. and static obstacle potential field coefficient , calculate the static obstacle collision risk potential field according to the following formula: ; Step 6: If it is a dynamic obstacle, the first warning signal is input into the dynamic obstacle collision risk potential field calculation unit, and the static obstacle spatial position is calculated. , dynamic obstacle potential field coefficient , relative speed and the relative motion vector angle , calculate the static obstacle collision risk potential field according to the following formula: ; ； Step 7: Substitute the vehicle position and speed into the static obstacle collision risk potential field and the dynamic obstacle risk potential field to determine whether it is within the dangerous potential field range. If it is within the safety threshold, end the occupant protection warning; Step 8: If it is within the dangerous potential field range, the second warning unit outputs a second warning signal; Step 9, after receiving the second warning signal, the virtual time-domain human injury prediction unit constructs a human injury prediction model according to the human injury database, wherein the human injury prediction model takes vehicle speed, collision angle, and collision position as inputs, and outputs the AIS levels of human head, chest, and leg injuries; Step 10, calculating the vehicle speed, collision angle, and collision position when the self-vehicle collides with the obstacle vehicle in the current vehicle state according to the static obstacle collision risk potential field and the dynamic obstacle risk potential field, and predicting the AIS level of human head, chest, and leg injuries in the current vehicle state through the human injury prediction model; Step 11, determine whether it is higher than a predetermined threshold, if it is lower, emergency braking is performed, if it is higher, the human body injury potential field calculation unit takes the obstacle as the center, establishes the human head, chest, and leg injury potential energy cloud, and the human head, chest, and leg injury potential energy cloud is constructed according to the following formula, and is related to the relative vehicle speed , velocity vector angle and The level is positively correlated; Step 12, superimpose the human head, chest, and leg injury potential energy clouds established respectively and assign correction factors in turn, the correction factors are empirical coefficients, and the correction factors corresponding to the head, chest, and leg injury potential energy clouds are reduced in turn to establish a human body injury potential field in: is the correction factor corresponding to the potential energy cloud of human head injury, is the correction factor corresponding to the human chest injury potential energy cloud, is the correction factor corresponding to the potential energy cloud of human leg injury; Step 13, the discrete path point prediction unit establishes a road coordinate system, takes the current centroid position of the vehicle as the starting path point, and the centroid position of the obstacle as the ending path point, discretizes the potential field range between the vehicle and the obstacle into a number of path points, and selects the path point with lower potential energy according to the established human body injury potential field; Step 14, the path fitting unit uses a polynomial to fit the path points with lower potential energy into the desired path; Step 15, controlling the wheel steering angle through the MPC controller to move along the desired path until reaching the end path point.

2. An occupant protection system based on human body injury potential field, characterized in that: The method for controlling the occupant protection system based on the human body injury potential field as claimed in claim 1 comprises: The occupant protection warning module is used to sense the driving environment and form a warning signal. The occupant protection warning module includes GPS, a speedometer, a laser radar, a first warning unit, a static obstacle collision risk potential field calculation unit, a dynamic obstacle risk potential field calculation unit and a second warning unit; An occupant protection planning module is used to plan a collision avoidance route with minimal human damage when the vehicle is about to have an unavoidable collision. The occupant protection planning module includes a virtual time domain human damage prediction unit, a human damage potential field calculation unit, and a discrete path point prediction unit; The occupant protection control module is used to control the vehicle to track the predicted collision avoidance trajectory, and the occupant protection control module includes a path fitting unit and an MPC controller.

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