A method for controlling braking of a driving training vehicle

Abstract

The present invention discloses a method for controlling the braking of a driving training vehicle, which mainly includes: obtaining the coordinates of the vehicle GPS main antenna and the vehicle heading angle information in real time through the vehicle-mounted dual GPS antenna, combining the distance from the vehicle GPS main antenna to the two corner points of the vehicle front and the two rear wheels of the vehicle, and calculating the real-time coordinates of the two corner points of the vehicle front and the two rear wheels of the vehicle; obtaining the vehicle speed data and the vehicle steering wheel angle data in real time, calculating the outer and inner turning radius of the vehicle according to the vehicle steering wheel angle data, calculating the vehicle prediction buffer length according to the vehicle speed data, and obtaining the vehicle's trajectory prediction buffer area in combination with the vehicle's steering; judging whether the obstacle is in the trajectory prediction buffer area according to the trajectory prediction buffer area and the coordinate information of the acquired obstacle, and if so, triggering a braking command. The present invention can realize the prejudgment of danger and timely intervention by calculating the pre-collision area through trajectory prediction, and improve the user experience of students' simulated driving.

Description

Technical Field

[0001] The invention relates to a method for controlling braking of a driving training vehicle, belonging to the technical field of vehicle collision safety. Background Art

[0002] As people's living standards continue to improve, convenient transportation has become a major demand of people, and travel safety is of paramount importance. Motor vehicle driving skills are receiving more and more attention from people. Every year, tens of thousands of students participate in professional driving skills training and obtain a driver's license after passing the motor vehicle driving skills test; passing the driving skills test can help drivers avoid traffic accidents while driving vehicles. The occurrence of accidents will not only have a certain impact on the vehicle itself, but also pose a very serious threat to people's safety and economy.

[0003] In the field of driving training, the robot coach training model has gradually replaced the traditional coach-led training model, thereby greatly reducing the cost of training. Currently, the robot coach systems on the market are equipped with safety protection units, which formulate safety strategies by obtaining sensor data. After the safety strategy is triggered, active braking is performed to prevent dangerous situations from occurring. Currently, the intervention timing of active braking in the market is relatively late, and the braking force is large, which can prevent danger, but the trainee experience is very poor. Summary of the invention

[0004] In order to solve the problem that the intervention timing of active braking in the existing motor vehicle driving training process is relatively late and the trainees' experience is very poor, the present invention provides a method for controlling the braking of a driving training vehicle, which can predict the danger and intervene in time by calculating the pre-collision area through trajectory prediction, thereby improving the user experience of trainees in simulated driving.

[0005] To achieve the above object, the present invention discloses a method for controlling the braking of a driving training vehicle, which mainly comprises:

[0006] Step S1, obtaining the coordinates of the vehicle's GPS main antenna and the vehicle's heading angle information in real time through the vehicle-mounted dual GPS antenna, and combining the distances from the vehicle's GPS main antenna to the two corner points of the vehicle's front and the two rear wheels of the vehicle to calculate the real-time coordinates of the two corner points of the vehicle's front and the two rear wheels of the vehicle;

[0007] Step S2, acquiring vehicle speed data and vehicle steering wheel angle data in real time, calculating the outer and inner turning radii of the vehicle according to the vehicle steering wheel angle data, calculating the vehicle predicted buffer length according to the vehicle speed data, and obtaining the vehicle trajectory predicted buffer area in combination with the vehicle steering;

[0008] Step S3: judging whether the obstacle is within the trajectory prediction buffer area according to the trajectory prediction buffer area and the acquired coordinate information of the obstacle, and if so, triggering a braking command.

[0009] The present invention has the following beneficial effects:

[0010] The method of the present invention can construct a trajectory prediction buffer area by predicting the trajectory, realize the prediction of dangerous situations, and thus perform braking intervention in a timely manner, thereby solving the problems of late intervention timing of active braking in the current motor vehicle driving training system, large braking force, and poor trainee experience.

[0011] The method of the present invention can realize accurate prediction of dangerous situations during driving training, can execute braking instructions at the optimal time point, avoid the occurrence of emergency braking and heavy stopping, greatly improve the students' driving learning experience, and improve the efficiency of driving training. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a schematic diagram of a vehicle turning left;

[0013] Figure 2 This is a schematic diagram of the vehicle turning right. DETAILED DESCRIPTION

[0014] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

[0015] The embodiment discloses a method for controlling the braking of a driving training vehicle, which mainly includes the following steps:

[0016] Step 1) The latitude and longitude coordinates of the vehicle's GPS main antenna (referred to as "GPS main antenna coordinates") and the vehicle's heading angle information are obtained in real time through the vehicle's dual GPS antennas, and the real-time coordinates of the two corner points of the front of the vehicle and the two rear wheels of the vehicle are calculated in combination with the distance from the vehicle's GPS main antenna to the two corner points of the front of the vehicle and the two rear wheels of the vehicle. It should be noted that the distance to the wheel in the present invention specifically refers to the distance to the center point of the wheel.

[0017] The specific calculation method of step 1) is as follows:

[0018] 11) Obtain the distance from the GPS main antenna to the front of the vehicle, the rear wheel axis, and the left and right sides of the vehicle body (specifically the ground projection distance) through manual measurement, that is, the vertical distance d from the GPS main antenna to the front of the vehicle f , the distance d from the GPS main antenna to the rear wheel axis b , the distance from the GPS main antenna to the left side of the vehicle body d l , the distance from the GPS main antenna to the right side of the vehicle body d r ;

[0019] 12) Calculate the real-time coordinates of the two corner points of the front of the vehicle and the two rear wheels of the vehicle through the GPS main antenna coordinates and the vehicle heading angle information;

[0020] The real-time coordinates of the left front corner of the vehicle are expressed as (x fl ,y fl ), where the horizontal and vertical coordinates are calculated as follows:

[0021] x fl =(x 0 -d l )cosθ-(y 0 +d f )sinθ;

[0022] y fl =(x 0 -d l )sinθ+(y 0 +d f )cosθ.

[0023] The real-time coordinates of the right front corner of the vehicle are expressed as (x fr ,y fr ), where the horizontal and vertical coordinates are calculated as follows:

[0024] x fr =(x 0 +d r )cosθ-(y 0 +d f )sinθ;

[0025] y fr =(x 0 +d r )sinθ+(y 0 +d f )cosθ.

[0026] The real-time coordinates of the right rear wheel of the vehicle are expressed as (x br ,y br ), where the horizontal and vertical coordinates are calculated as follows:

[0027] x br =(x 0 +d r )cosθ-(y 0 +d b )sinθ;

[0028] y br =(x 0 +d r )sinθ+(y 0 +d b )cosθ.

[0029] The real-time coordinates of the left rear wheel of the vehicle are expressed as (x bl ,y bl ), where the horizontal and vertical coordinates are calculated as follows:

[0030] x bl =(x 0 -d l )cosθ-(y 0 +d b )sinθ;

[0031] y bl =(x 0 -d l )sinθ+(y 0 +d b )cosθ.

[0032] In the formula, (x 0 ,y 0 ) is the coordinate of the GPS main antenna, and θ is the vehicle heading angle.

[0033] Step 2) The vehicle steering wheel angle data and the vehicle speed data are obtained in real time, and the front wheel angle of the vehicle is obtained according to the correspondence between the front wheel of the vehicle and the steering wheel angle. Based on the front wheel angle of the vehicle and the speed data of the vehicle, the predicted trajectories of the two corner points of the front of the vehicle and the two rear wheels of the vehicle are drawn respectively, and the trajectory prediction buffer area of ​​the vehicle is obtained in combination with the steering of the vehicle.

[0034] Step 2) specifically includes the following steps:

[0035] 21) The vehicle steering wheel angle data is obtained in real time through the vehicle steering wheel sensor, and the vehicle front wheel angle is calculated based on this. The calculation formula is as follows:

[0036] α = k × S;

[0037] Wherein, α is the front wheel angle; S is the steering wheel angle; k is the measurement parameter, which can be in the range of 0.02 to 0.03, for example, the k value is 0.025;

[0038] It should be noted that, since the vehicle is traveling at a low speed in the driving training scenario of Subject 2, the steering wheel angle and the front wheel angle are considered to be linearly related in the present invention, and the left and right front wheel angles are equal.

[0039] 22) According to the Ackerman steering principle in vehicle engineering, the turning radius on the outside and inside of the vehicle is calculated:

[0040] OR = l / tanα;

[0041] IR = OR-w;

[0042] Where, OR is the turning radius on the outside of the vehicle, IR is the turning radius on the inside of the vehicle, l is the wheelbase, and w is the width of the vehicle.

[0043] 23) The vehicle speed information is obtained in real time through the vehicle OBD interface, and the buffer length is calculated based on the vehicle speed. The minimum buffer length is 1 meter. The specific calculation is as follows:

[0044] l h =max(0.4v,1);

[0045] In the formula, l h is the predicted buffer length, v is the vehicle speed;

[0046] It should be noted that the predicted buffer length here refers to the length of the vehicle's driving trajectory during the braking process to a standstill. Since the predicted trajectory is usually an arc, the corresponding predicted buffer length is also the arc length value. In addition, there is no strict order requirement for step 23) and step 21) and step 22).

[0047] 24) Draw the predicted trajectories of the two corner points of the front of the vehicle and the two rear wheels of the vehicle respectively, and select the predicted trajectories of the two corner points of the front of the vehicle and the corresponding rear wheels of the vehicle to close according to the vehicle steering to form a predicted buffer area.

[0048] For the convenience of calculation, under the premise of meeting the accuracy requirements, the predicted trajectories of the two corner points of the front of the vehicle and the two rear wheels of the vehicle can be approximated as an arc segment composed of 10 points. Of course, the number of points that make up the arc segment can also be adjusted according to the accuracy requirements. The coordinates of each point on the arc segment (referred to as "arc segment point") are calculated as follows:

[0049] Calculate the angle β corresponding to the i-th point on the turning radius arc segment outside the vehicle Oi :

[0050]

[0051] Calculate the angle β corresponding to the i-th point on the turning radius arc segment inside the vehicle Ii :

[0052]

[0053] In the formula, i=1,…,10.

[0054] When the vehicle turns left, the left wheel of the vehicle is turned inside and the right wheel is turned outside. Specifically:

[0055] The arc point of the right rear wheel of the vehicle (x bri ,y bri ) is calculated as follows:

[0056] x bri=x br *cosβ Oi -y br *sinβ Oi ;

[0057] y bri =x br *sinβ Oi +y br *cosβ Oi .

[0058] The arc point of the left rear wheel of the vehicle (x bli ,y bli ) is calculated as follows:

[0059] x bli =x bl *cosβ Ii -y bl *sinβ Ii ;

[0060] y bli =x bl *sinβ Ii +y bl *cosβ Ii .

[0061] The arc point of the right front corner of the vehicle head (x fri ,y fri ) is calculated as follows:

[0062] x fri =x bri +y fr -y br ;

[0063] y fri =y bri .

[0064] The arc point of the left front corner of the vehicle head (x fli ,y fli ) is calculated as follows:

[0065] x fli =x bli +y fl -y bl

[0066] y fli =y bli .

[0067] Based on the above calculation formula, the predicted trajectories corresponding to the right rear wheel, the left rear wheel, the right front corner point of the vehicle head, and the left front corner point of the vehicle head can be obtained. Based on these four predicted trajectories, combined with the vehicle's left turn status, the predicted trajectories of the two corner points of the vehicle head and the left rear wheel are selected for closure. Figure 1 As shown, specifically, the five arc points of the farthest arc point fl10 at the left front corner of the vehicle, the farthest arc point fr10 at the right front corner of the vehicle, the closest arc point fr1 at the right front corner of the vehicle, the closest arc point bl1 at the left rear wheel of the vehicle, and the farthest arc point bl10 at the left rear wheel of the vehicle are connected in sequence, and the enclosed area is the trajectory prediction buffer area.

[0068] When the vehicle turns right, the right wheel is turned inside and the left wheel is turned outside. Specifically:

[0069] The arc point of the right rear wheel of the vehicle (x bri ,y bri ) is calculated as follows:

[0070] x bri =x br *cosβ Ii -y br *sinβ Ii

[0071] y bri =x br *sinβ Ii +y br *cosβ Ii .

[0072] The arc point of the left rear wheel of the vehicle (x bli ,y bli ) is calculated as follows:

[0073] x bli =x bl *cosβ Oi -y bl *sinβ Oi ;

[0074] y bli =x bl *sinβ Oi +y bl *cosβ Oi .

[0075] The arc point of the right front corner of the vehicle head (x fri ,y fri ) is calculated as follows:

[0076] x fri =x bri +y fr -ybr ;

[0077] y fri =y bri .

[0078] The arc point of the left front corner of the vehicle head (x fli ,y fli ) is calculated as follows:

[0079] x fli =x bli +y fl -y bl ;

[0080] y fli =y bli .

[0081] In the formula, x fli ,y fli are the coordinate values ​​of the i-th arc point of the left front corner of the vehicle head; fri ,y fri are the coordinate values ​​of the i-th arc point of the right front corner of the vehicle head; bri ,y bri are the coordinate values ​​of the i-th arc point of the right rear wheel of the vehicle; x bli ,y bli are the coordinate values ​​of the i-th arc point of the left rear wheel of the vehicle.

[0082] Based on the above calculation formula, the predicted trajectories corresponding to the right rear wheel, the left rear wheel, the right front corner point of the vehicle, and the left front corner point of the vehicle can be obtained. Based on these four predicted trajectories, combined with the right turn state of the vehicle, the predicted trajectories of the two corner points of the vehicle front and the right rear wheel are selected for closure. Figure 2 As shown, specifically, the five arc points fl1, the closest arc point of the left front corner of the vehicle, fl10, the farthest arc point of the left front corner of the vehicle, fr10, the farthest arc point of the right front corner of the vehicle, bl10, the farthest arc point of the left rear wheel of the vehicle, and bl1, the closest arc point of the left rear wheel of the vehicle, are connected in sequence, and the enclosed area is the trajectory prediction buffer area.

[0083] Step 3) judging whether the obstacle enters the trajectory prediction buffer area according to the trajectory prediction buffer area and the coordinate information of the obstacle obtained by the vehicle-mounted sensor, and if so, triggering a braking command.

[0084] Specifically, the trajectory prediction buffer area obtained in step 2) is combined with the coordinate information of the obstacle obtained by the vehicle-mounted millimeter-wave radar to determine the relationship between the point representing the obstacle and the predicted buffer area. If the point is within the predicted buffer area, it means that the obstacle enters the trajectory prediction buffer area, and the braking command is executed through the vehicle braking system.

[0085] Finally, it should be noted that, although the embodiments of the present invention are described above, the present invention is not limited to the above specific embodiments and application fields, and the above specific embodiments are only illustrative and instructive, but not restrictive. Under the guidance of this specification, a person skilled in the art can make many forms without departing from the scope of protection of the claims of the present invention, all of which belong to the protection of the present invention.

Claims

1. A method for controlling the braking of a driving training vehicle, characterized in that: include: Step S1, obtaining the coordinates of the vehicle's GPS main antenna and the vehicle's heading angle information in real time through the vehicle-mounted dual GPS antenna, and combining the distances from the vehicle's GPS main antenna to the two corner points of the vehicle's front and the two rear wheels of the vehicle to calculate the real-time coordinates of the two corner points of the vehicle's front and the two rear wheels of the vehicle; Step S2, acquiring vehicle speed data and vehicle steering wheel angle data in real time, calculating the outer and inner turning radii of the vehicle according to the vehicle steering wheel angle data, calculating the vehicle predicted buffer length according to the vehicle speed data, and obtaining the vehicle trajectory predicted buffer area in combination with the vehicle steering; Step S3, judging whether the obstacle is within the trajectory prediction buffer area according to the trajectory prediction buffer area and the acquired coordinate information of the obstacle, and if so, triggering a braking command; The step S1 specifically includes: Get the distance d from the GPS main antenna to the front of the vehicle f , the distance d from the GPS main antenna to the rear wheel axis b , the distance from the GPS main antenna to the left side of the vehicle body d l , the distance from the GPS main antenna to the right side of the vehicle body d r ; Through the GPS main antenna coordinates and vehicle heading angle information, the real-time coordinates of the two corner points of the front of the vehicle and the two rear wheels of the vehicle are calculated as follows: Among them, the real-time coordinates of the left front corner of the vehicle are expressed as (x fl ,y fl ): x fl =(x0-d l )cosθ-(y0+d f )sinθ, y fl =(x0-d l )sinθ+(y0+d f )cosθ; Among them, the real-time coordinates of the right front corner of the vehicle are expressed as (x fr ,y fr ): x fr =(x0+d r )cosθ-(y0+d f )sinθ, y fr =(x0+d r )sinθ+(y0+d f )cosθ Among them, the real-time coordinates of the right rear wheel of the vehicle are expressed as (x br ,y br ): x br =(x0+d r )cosθ-(y0+d b )sinθ, y br =(x0+d r )sinθ+(y0+d b )cosθ; Among them, the real-time coordinates of the left rear wheel of the vehicle are expressed as (x bl ,y bl ): x bl =(x0-d l )cosθ-(y0+d b )sinθ, y bl =(x0-d l )sinθ+(y0+d b )cosθ; Where (x0, y0) is the coordinate of the GPS main antenna, and θ is the vehicle heading angle; The step S2 specifically includes: The vehicle steering wheel angle data is obtained in real time, and the vehicle front wheel angle is obtained according to the corresponding relationship between the vehicle front wheel and the steering wheel angle. The calculation formula is: α=k×S Wherein, α is the front wheel turning angle; S is the steering wheel turning angle; k is the measurement parameter; when the vehicle turns, the angle values ​​of the left turning angle and the right turning angle in the front wheel turning angle are equal; According to the Ackerman steering principle in vehicle engineering, the vehicle outer turning radius OR and the vehicle inner turning radius IR are calculated respectively: OR=l / tanα IR=OR-w Where l is the wheelbase of the vehicle, and w is the width of the vehicle; Obtain vehicle speed data in real time and calculate the predicted buffer length l based on the vehicle speed h , the predicted buffer length l h The minimum is 1 meter, and the calculation formula is: l h =max(0.4v,1) Where, v is the vehicle speed; Based on the vehicle outer turning radius OR, the vehicle inner turning radius R, and the predicted buffer length l h , respectively draw the predicted trajectories of the two corner points of the front of the vehicle and the two rear wheels of the vehicle, and select the two corner points of the front of the vehicle and the corresponding predicted trajectories of the rear wheels of the vehicle to be closed in combination with the steering direction of the vehicle to form the predicted buffer area; In step S2: Based on the vehicle outer turning radius OR, the vehicle inner turning radius R, and the predicted buffer length l h , respectively draw the predicted trajectories of the two corner points of the front of the vehicle and the two rear wheels of the vehicle, select the corresponding predicted trajectories of the rear wheels of the vehicle and the two corner points of the front of the vehicle in combination with the steering of the vehicle to close the predicted trajectories, and form the predicted buffer area, which specifically includes: The predicted trajectories of the left front wheel and the right front wheel of the vehicle are approximated as arc segments consisting of N points; Calculate the angle β corresponding to the i-th point on the turning radius arc segment outside the vehicle oi , and the angle β corresponding to the i-th point on the turning radius arc segment inside the vehicle Ii ; Wherein, i=1,...,N; When the vehicle turns left, the left wheel of the vehicle turns inside and the right wheel turns outside. The coordinates of each point on the arc segment, that is, the coordinates of the arc segment points, are calculated, where: The arc point of the right rear wheel of the vehicle (x bri ,y bri ) is calculated as follows: x bri =x br *cosβ Oi -y br *sinβ Oi ; y bri =x br *sinβ Oi +y br *coSβ Oi ; The arc point of the left rear wheel of the vehicle (x bli ,y bli ) is calculated as follows: x bli =x bl *cosβ Ii -y bl *sinβ Ii ; y bli =x bl *sinβ Ii +y bl *cosβ Ii ; The arc point of the right front corner of the vehicle head (x fri ,y fri ) is calculated as follows: x fri =x bri +y fr -and br ; and fri =and bri ; The arc point of the left front corner of the vehicle (x fli ,y fli ) is calculated as follows: x fli =x bli +y fl -and bl and fli =and bli ; Thus, the predicted trajectories corresponding to the right rear wheel, the left rear wheel, the right front corner point of the front of the vehicle, and the left front corner point of the front of the vehicle are obtained; in combination with the left turn of the vehicle, the predicted trajectories of the two corner points of the front of the vehicle and the left rear wheel are selected to be closed to form the predicted buffer area; When the vehicle turns right, the right wheel is turned inside and the left wheel is turned outside. The coordinates of each point on the arc segment, that is, the coordinates of the arc segment points, are calculated, where: The arc point of the right rear wheel of the vehicle (x bri ,y bri ) is calculated as follows: x bri =x br *cosβ Ii -y br *sinβ Ii y bri =x br *sinβ Ii +y br *coSβ Ii ; The arc point of the left rear wheel of the vehicle (x bli ,y bli ) is calculated as follows: x bli =x bl *cosβ Oi -y bl *sinβ Oi ; y bli =x bl *sinβ Oi +y bl *cOsβ Oi ; The arc point of the right front corner of the vehicle head (x fri ,y fri ) is calculated as follows: x fri =x bri +y fr -and br ; and fri =and bri ; The arc point of the left front corner of the vehicle (x fli ,y fli ) is calculated as follows: x fli =x bli +y fl -and bl ; and fli =and bli ; Thus, the predicted trajectories corresponding to the right rear wheel, the left rear wheel, the right front corner point of the front of the vehicle, and the left front corner point of the front of the vehicle are obtained; combined with the right turn of the vehicle, the predicted trajectories of the two corner points of the front of the vehicle and the right rear wheel are selected to be closed to form the predicted buffer area.

2. The method for controlling the braking of a driving training vehicle according to claim 1, characterized in that: The distance d from the GPS main antenna to the front of the vehicle is obtained by manual measurement. f , the distance d from the GPS main antenna to the rear wheel axis b , the distance from the GPS main antenna to the left side of the vehicle body d l , the distance from the GPS main antenna to the right side of the vehicle body d r .

3. The method for controlling braking of a driving training vehicle according to claim 1, characterized in that: The value range of the measurement parameter k is 0.02 to 0.

03.

4. The method for controlling the braking of a driving training vehicle according to claim 1, characterized in that: The N is 10.

5. The method for controlling braking of a driving training vehicle according to any one of claims 1 to 4, characterized in that: The vehicle steering wheel angle data is obtained in real time through the vehicle steering wheel sensor, and the vehicle speed data is obtained in real time through the vehicle OBD interface.

6. The method for controlling braking of a driving training vehicle according to any one of claims 1 to 4, characterized in that: In step S3, the coordinate information of the obstacle is obtained by using the vehicle-mounted millimeter wave radar.

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