CN112606833A - Model prediction control-based intelligent vehicle motion control method for protecting human-ground collision damage - Google Patents
Model prediction control-based intelligent vehicle motion control method for protecting human-ground collision damage Download PDFInfo
- Publication number
- CN112606833A CN112606833A CN202011519629.9A CN202011519629A CN112606833A CN 112606833 A CN112606833 A CN 112606833A CN 202011519629 A CN202011519629 A CN 202011519629A CN 112606833 A CN112606833 A CN 112606833A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- human
- chest
- human body
- motion
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W2030/082—Vehicle operation after collision
Abstract
Aiming at the defects of the existing vehicle motion control method for protecting the human-ground collision damage, the intelligent vehicle motion control method for protecting the human-ground collision damage based on model prediction control is provided. When the accident is monitored to be unavoidable, completely braking the vehicle to a time t1 when the head of the person collides with the vehicle; then releasing the vehicle brake and monitoring the speed and the position of the chest of the human body in real time, predicting the motion track of the chest of the human body within 10 time steps, and controlling the transverse and longitudinal motion of the vehicle according to the difference between the predicted track and the position of the head of the vehicle; when the chest position of the human body is monitored to be higher than the front edge height of the engine cover, the track estimation and motion control steps are repeated; when the chest position of the human body is detected to be lower than the front edge of the engine cover, the vehicle is completely braked to be static. The invention has the beneficial effects that: the transverse and longitudinal motion of the vehicle is controlled according to the estimated track, and the problem that the transverse control of the vehicle is not considered in the existing achievement and the high-efficiency control is difficult to implement due to the extremely short accident process is effectively solved.
Description
Technical Field
The invention relates to the field of intelligent automobiles, in particular to a model prediction control-based intelligent automobile motion control method for protecting human-ground collision damage.
Background
The intelligent automobile is provided with good wishes of people for road traffic safety, intelligence, high efficiency and the like from the beginning, and people expect to greatly reduce the number of traffic accidents through the intelligent automobile and realize the vision of zero accidents. In the intelligent era, it is certain that the number of accidents is greatly reduced and the collision speed is also greatly reduced, but from the current research on accident data, the automatic emergency braking system of pedestrians and the practical situation of running of a small number of automobiles (such as Tesla) with certain intelligence, the intelligent automobile has a long distance from the zero accident landscape.
People expect the intelligent vehicle very much, and the intelligent vehicle can greatly reduce the number of collision accidents such as vehicles, particularly the collision vehicle speed, so as to protect passengers better, but because the effect of protecting pedestrians is certainly not as obvious as the effect of protecting passengers due to the unpredictability of pedestrians, the pedestrian protection capability of the intelligent vehicle before realizing the zero accident vision needs to be improved urgently, so as to realize the protection of weak road users by traffic intensity.
In the event of a human-vehicle collision, studies have shown that pedestrian injury results from a first impact with the vehicle followed by a second impact with the ground. However, in the event of a low speed collision, the human body injury is more likely to result from the impact with the ground, and the deep accident investigation results further show that the accident loss can be reduced 2/3 if the ground injury can be avoided. Therefore, researchers have conducted extensive and intensive studies on the human-ground collision damage mechanism, the human-ground collision high-precision simulation modeling, the human-ground collision damage protection method, and the like. In the aspect of damage protection, parts such as a roof and an engine cover, and intelligent vehicle motion control methods such as brake control and speed control are proposed to effectively reduce human-ground collision damage in an accident. The remarkable feature of these research results, especially the related results on vehicle motion control, is that they only control the longitudinal direction of the vehicle and do not consider the current situation that the accident process is very short, which makes it difficult to implement efficient control. After the human-vehicle collision happens, the time of the human head contacting the vehicle body happens within a few tenths of a second, then the human body is thrown out and falls down to the ground, the whole process is completed within a very short time, and the intelligent vehicle is required to scientifically control the self-movement to reduce the difficulty of human-ground collision damage to the maximum extent. Under the condition, the model prediction control concept can be applied, the approximate motion track of the human body after the pedestrian is thrown out is predicted, the motion of the vehicle is controlled by taking the approximate motion track as a target, and the damage caused by the ground is effectively reduced.
Disclosure of Invention
Aiming at the current situation that the existing intelligent vehicle motion control method for protecting human-ground collision damage does not control the vehicle transversely and does not consider the problem that the high-efficiency control is difficult to implement due to the extremely short accident process, the invention provides an intelligent vehicle motion control method for protecting human-ground collision damage based on model predictive control, which comprises the following implementation steps:
s1: when the vehicle monitors that the accident is unavoidable, the vehicle is completely braked to the t1 moment when the head of the human body collides with the vehicle body for the first time, the vehicle brake is released after t1, and the speed and the position of the chest of the human body in the x, y and z directions are monitored in real time;
s2: estimating the motion trail of the human chest within 10 time steps after the time according to the speeds vx0, vy0 and vz0 and the positions px0, py0 and pz0 of the human chest in the x, y and z directions monitored at the time t 1;
s3: calculating the difference e1 between the chest position of the human body and the rear edge position of the engine hood in the x direction in the motion trail obtained in the step S2, and dividing the difference e1 into a positive type, a zero type and a negative type; meanwhile, calculating the difference e2 between the chest position of the human body and the middle position of the rear edge of the engine hood in the y direction in the obtained motion trail, and dividing the difference e2 into seven types of negative big, negative middle, negative small, zero, positive small, positive middle and positive big;
s4: controlling the motion of the vehicle in the x direction according to a given rule, and controlling the motion of the vehicle in the y direction according to given steps after the human-vehicle is out of contact; meanwhile, the speed and the position of the chest of the human body in the x direction, the y direction and the z direction are continuously monitored in real time;
s5: when the position of the chest of the human body in the z direction is detected to be higher than the front edge height of the engine hood, replacing t1 with the current real-time, and repeating the steps S2, S3 and S4;
s6: when the position of the human chest in the z direction is detected to be lower than the front edge height of the engine hood, the vehicle is completely braked to be stationary.
When an accident is monitored to be unavoidable, the invention requires that the vehicle is completely braked to the t1 moment when the head of the human body collides with the vehicle body; then releasing vehicle brake, monitoring the speed and position of the human chest in the x direction, the y direction and the z direction in real time, predicting the motion track of the human chest within 10 time steps after the moment according to the monitored speed and position of the human chest, and further calculating the position difference e1 of the human chest and the vehicle body in the x direction and the position difference e2 in the y direction in the motion track; then controlling the longitudinal motion of the vehicle according to e1 and controlling the transverse motion of the vehicle according to e 2; when the chest position of the human body is monitored to be higher than the front edge height of the engine cover, the steps of estimating the chest movement track of the human body and controlling the transverse and longitudinal movement of the vehicle are repeated; when the chest position of the human body is detected to be lower than the front edge of the engine cover, the vehicle is completely braked to be static; therefore, the aim of influencing the falling posture of the human body by moving the vehicle and further protecting the human body from collision and injury is fulfilled.
Preferably, in step S1, t1 is the time when the head of the human body makes contact with the vehicle body for the first time, and the vehicle is completely braked before the time node, so that on one hand, the speed of the head-vehicle collision time in the human body head-vehicle collision accident can be reduced as much as possible, and thus the head damage is reduced; on the other hand, the vehicle can be ensured to be in a complete braking state (because the monitoring of the vehicle cannot reach t1) in the accident that the head of the human body does not collide with the vehicle body (such as the human body collides with the side face of the vehicle), namely, the vehicle does not need to be controlled in the accident and only needs to be completely braked.
Preferably, in steps S1 to S6, the x direction indicates the vehicle longitudinal direction at the moment of the human-vehicle collision and is directed to the vehicle advancing direction; the y direction is vertical to the x direction and points to the left side of a driver of the vehicle in the instant of collision of people and the vehicle; the z direction is vertical to the plane defined by the x and the y and points to the upper part of the ground; the position of the human thorax in the x, y and z directions is determined by the coordinates (px, py, pz) of the thorax in a cartesian rectangular coordinate system (x, y, z), the origin of which coincides with the projection of the position of the center of gravity of the vehicle on the ground at the moment of the human-vehicle collision.
Preferably, the estimation method of the motion trail of the human chest in step S2 is as follows:
assuming that the chest of the human body monitored in real time at the time t has the velocities vx0, vy0 and vz0 in the x, y and z directions and the positions px0, py0 and pz0, the chest positions of the human body at the time t +1 are as follows:
px1＝px0+vx0×Ts,
py1＝py0+vy0×Ts,
pz1＝pz0+vz0×Ts-g×Ts×Ts/2,
in the formula, g is the local gravity acceleration, Ts is the time step length, and the time step length is determined according to the sampling frequency of the intelligent vehicle monitoring equipment; and the motion trail of the chest of the human body within 10 time steps after the t moment can be obtained by calculating 10 times by analogy.
Preferably, in step S3, negative big finger e2< -0.5m, negative middle finger-0.5 m < e2< -0.3m, negative little finger-0.3 m < e2<0m, positive little finger 0m < e2<0.3m, middle finger 0.3m < e2<0.5m, and positive big finger e2>0.5 m.
Preferably, in step S4, the motion control rule of the vehicle in the x direction is: when e1 is positive, the vehicle is accelerated, and the acceleration value is 1m/s2(ii) a When e1 is negative, the vehicle is decelerated, and the acceleration value is taken as-1 m/s2(ii) a When e1 is zero, controlling the acceleration of the vehicle to be zero; in the process, when the vehicle detects that an obstacle or the positions of the head, the chest, the hip and the like of the human body in front are lower than the front edge of the engine hood, the motion control in the x direction is finished, and the vehicle is completely braked. In each time step, the rear edge of the engine cover is ensured to be at the same position with the chest of the human body by adjusting the acceleration of the vehicle, so that the pedestrian can be caught after the time t 1. When the vehicle monitors that the front obstacle exists, the vehicle is completely braked in order to avoid other potential risks; when the vehicle monitors that the positions of the head, the chest, the hip and the like of the human body are lower than the engine cover, the human body is not thrown up or is about to fall off the ground, and at the moment, the vehicle needs to be completely braked to avoid the vehicle from pushing the human body to move forward to transmit more kinetic energy to the human body or crush the human body.
Preferably, in step S4, the motion control step of the vehicle in the y direction is:
s41: when the condition that e2 is not zero is monitored, a message is sent to the surrounding vehicles to give a clear lane change intention;
s42: when the people and the vehicle are separated from contact, the surrounding environment is monitored, and the transverse motion of the vehicle is controlled according to the following rules on the premise of confirming safety: if e2 is negative, setting the steering angle of the wheels to-15 degrees; if e2 is negative-medium, the steering angle of the wheels is set to-10 degrees; if e2 is negative, setting the steering angle of the wheels to be-5 degrees; if e2 is zero, setting the wheel steering angle to zero; if e2 is positive small, the wheel steering angle is set to 5 °; if e2 is in the middle, setting the steering angle of the wheels to 10 degrees; if e2 is positive, setting the wheel steering angle to 15 °; the vehicle steering angle is positive counterclockwise. Compared with longitudinal control, the transverse motion control of the vehicle is only carried out after the human and the vehicle are separated from contact, and the values of the wheel turning angles are large in order to control the position of the vehicle in a short time. From the perspective of a driver, when a human body deviates to the left side of the vehicle, the vehicle is moved leftwards, otherwise, the vehicle is moved rightwards, and finally the position difference between the vehicle and the vehicle is zero, so that the human body can finally fall into the center of the engine cover rather than falling onto the ground from the edge of the vehicle body, and the optimal vehicle body pick-up position is achieved.
S43: and after the contact of the human and the vehicle is monitored, setting the steering angle of the wheels to be zero, and finishing the transverse motion control. After the people and the vehicle are contacted, the people and the vehicle can be influenced mutually due to the action of friction force, the transverse motion of the vehicle is controlled at the moment, the speed of the human body in the y direction can be increased, the kinetic energy of the human body obtained from the vehicle body in the whole process can be increased, and the risk of human collision and damage can be increased. This is a dangerous behaviour and therefore the vehicle lateral motion control is only implemented after the human vehicle has left contact.
Preferably, when the position of the chest of the human body in the z direction is detected to be higher than the front edge height of the engine hood in the step S5, the human body is still away from the falling ground for a period of time, so that the braking control of the vehicle can be continued; considering that the pedestrian motion trajectory model is simple, in order to ensure the accuracy of the model, the motion trajectory of the human body within 10 time steps after the current real-time is calculated again according to step S2, and the control of the vehicle motion in steps S3 and S4 is continued accordingly.
Preferably, when the position of the chest of the human body in the z direction is detected to be lower than the front edge height of the engine hood in step S6, it indicates that the human body is about to fall to the ground, and the vehicle is fully braked to avoid a crush accident.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that: the motion track of the human body in the next 10 time step lengths is predicted according to the monitored chest speed and position of the human body, and the high-efficiency control of the vehicle motion is realized by scientifically adjusting the acceleration and the steering angle of the wheels, so that the problem that the high-efficiency control is difficult to implement due to the fact that the transverse control of the vehicle and the extremely short accident process are not considered in the existing achievement is effectively solved.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
the technical solution of the present invention is further described below with reference to examples.
For a certain intelligent automobile, when the intelligent automobile monitors that potential collision with a pedestrian is unavoidable, the method comprises the following steps of:
s1: and (3) fully braking the vehicle to t1 moment when the head of the human body collides with the vehicle body for the first time, releasing the vehicle brake after t1 and monitoring the speed and the position of the chest of the human body in the x direction, the y direction and the z direction in real time. Wherein the x direction refers to the longitudinal direction of the vehicle at the moment of collision of the man and the vehicle and points to the advancing direction of the vehicle; the y direction is vertical to the x direction and points to the left side of a driver of the vehicle in the instant of collision of people and the vehicle; the z direction is vertical to the plane defined by the x and the y and points to the upper part of the ground; the position of the human thorax in the x, y and z directions is determined by the coordinates (px, py, pz) of the thorax in a cartesian rectangular coordinate system (x, y, z), the origin of which coincides with the projection of the position of the center of gravity of the vehicle on the ground at the moment of the human-vehicle collision.
S2: and estimating the motion trail of the human chest within 10 time steps after the time according to the speeds vx0, vy0 and vz0 of the human chest in the x, y and z directions and the positions px0, py0 and pz0 monitored at the time t 1. The estimation method comprises the following steps:
assuming that the chest of the human body monitored in real time at the time t has the velocities vx0, vy0 and vz0 in the x, y and z directions and the positions px0, py0 and pz0, the chest positions of the human body at the time t +1 are as follows:
px1＝px0+vx0×Ts,
py1＝py0+vy0×Ts,
pz1＝pz0+vz0×Ts-g×Ts×Ts/2,
in the formula, g is the local gravity acceleration, Ts is the time step length, and the time step length is determined according to the sampling frequency of the intelligent vehicle monitoring equipment; calculating 10 times by analogy, the motion track of the human chest within 10 time steps after the t moment can be obtained
S3: calculating the difference e1 between the chest position of the human body and the rear edge position of the engine hood in the x direction in the motion trail obtained in the step S2, and dividing the difference e1 into a positive type, a zero type and a negative type; meanwhile, the difference e2 between the chest position of the human body and the middle position of the rear edge of the engine hood in the y direction in the obtained motion trail is calculated, and the difference e2 is divided into seven types of negative large, negative middle, negative small, zero, positive small, positive middle and positive large. Wherein, the negative big finger e2< -0.5m, the negative middle finger-0.5 m < e2< -0.3m, the negative little finger-0.3 m < e2<0m, the positive little finger 0m < e2<0.3m, the middle finger 0.3m < e2<0.5m, and the positive big finger e2>0.5 m.
S4: controlling the motion of the vehicle in the x direction according to a given rule, and controlling the motion of the vehicle in the y direction according to given steps after the human-vehicle is out of contact; meanwhile, the speed and the position of the chest of the human body in the x direction, the y direction and the z direction are continuously monitored in real time.
The motion control rule of the vehicle in the x direction is as follows: when e1 is positive, the vehicle is accelerated, and the acceleration value is 1m/s2(ii) a When e1 is negative, the vehicle is decelerated, and the acceleration value is taken as-1 m/s2(ii) a When e1 is zero, controlling the acceleration of the vehicle to be zero; in the process, when the vehicle detects that an obstacle or the positions of the head, the chest, the hip and the like of the human body in front are lower than the front edge of the engine hood, the motion control in the x direction is finished, and the vehicle is completely braked.
The motion control steps of the vehicle in the y direction are as follows:
s41: when the condition that e2 is not zero is monitored, a message is sent to the surrounding vehicles to give a clear lane change intention;
s42: when the people and the vehicle are separated from contact, the surrounding environment is monitored, and the transverse motion of the vehicle is controlled according to the following rules on the premise of confirming safety: if e2 is negative, setting the steering angle of the wheels to-15 degrees; if e2 is negative-medium, the steering angle of the wheels is set to-10 degrees; if e2 is negative, setting the steering angle of the wheels to be-5 degrees; if e2 is zero, setting the wheel steering angle to zero; if e2 is positive small, the wheel steering angle is set to 5 °; if e2 is in the middle, setting the steering angle of the wheels to 10 degrees; if e2 is positive, setting the wheel steering angle to 15 °; the vehicle steering angle is positive counterclockwise.
S43: and after the contact of the human and the vehicle is monitored, setting the steering angle of the wheels to be zero, and finishing the transverse motion control.
S5: when the position of the chest of the human body in the z direction is detected to be higher than the front edge height of the engine hood, replacing t1 with the current real-time, and repeating the steps S2, S3 and S4;
s6: when the position of the human chest in the z direction is detected to be lower than the front edge height of the engine hood, the vehicle is completely braked to be stationary.
The invention provides an intelligent vehicle motion control method for protecting human-ground collision damage based on model predictive control, when an accident is monitored to be unavoidable, the method requires that a vehicle is completely braked to a t1 moment when the head of a human body collides with a vehicle body; then releasing vehicle brake, monitoring the speed and position of the human chest in the x direction, the y direction and the z direction in real time, predicting the motion track of the human chest within 10 time steps after the moment according to the monitored speed and position of the human chest, and further calculating the position difference e1 of the human chest and the vehicle body in the x direction and the position difference e2 in the y direction in the motion track; then controlling the longitudinal motion of the vehicle according to e1 and controlling the transverse motion of the vehicle according to e 2; when the chest position of the human body is monitored to be higher than the front edge height of the engine cover, the steps of estimating the chest movement track of the human body and controlling the transverse and longitudinal movement of the vehicle are repeated; when the chest position of the human body is detected to be lower than the front edge of the engine cover, the vehicle is completely braked to be static; therefore, the aim of influencing the falling posture of the human body by moving the vehicle and further protecting the human body from collision and injury is fulfilled.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (6)
1. The model predictive control-based intelligent vehicle motion control method for protecting human-ground collision damage is characterized by comprising the following steps of: according to the estimated human motion track, the transverse and longitudinal motions of the vehicle are controlled by adjusting the acceleration and the steering angle, the moving vehicle can be ensured to influence the kinematic response of the human body in the human-vehicle collision, and further the human-ground collision damage is protected, and the specific implementation steps are as follows:
s1: when the vehicle monitors that the accident is unavoidable, the vehicle is completely braked to the t1 moment when the head of the human body collides with the vehicle body for the first time, the vehicle brake is released after t1, and the speed and the position of the chest of the human body in the x, y and z directions are monitored in real time;
s2: estimating the motion trail of the human chest within 10 time steps after the time according to the speeds vx0, vy0 and vz0 and the positions px0, py0 and pz0 of the human chest in the x, y and z directions monitored at the time t 1;
s3: calculating the difference e1 between the chest position of the human body and the rear edge position of the engine hood in the x direction in the motion trail obtained in the step S2, and dividing the difference e1 into a positive type, a zero type and a negative type; meanwhile, calculating the difference e2 between the chest position of the human body and the middle position of the rear edge of the engine hood in the y direction in the obtained motion trail, and dividing the difference e2 into seven types of negative big, negative middle, negative small, zero, positive small, positive middle and positive big;
s4: controlling the motion of the vehicle in the x direction according to a given rule, and controlling the motion of the vehicle in the y direction according to given steps after the human-vehicle is out of contact; meanwhile, the speed and the position of the chest of the human body in the x direction, the y direction and the z direction are continuously monitored in real time;
s5: when the position of the chest of the human body in the z direction is detected to be higher than the front edge height of the engine hood, replacing t1 with the current real-time, and repeating the steps S2, S3 and S4;
s6: when the position of the human chest in the z direction is detected to be lower than the front edge height of the engine hood, the vehicle is completely braked to be stationary.
2. The intelligent vehicle motion control method for protecting human-ground collision damage based on model predictive control according to claim 1, characterized in that: in steps S1 to S6, the x direction indicates the vehicle longitudinal direction at the moment of the human-vehicle collision and points in the vehicle forward direction; the y direction is vertical to the x direction and points to the left side of a driver of the vehicle in the instant of collision of people and the vehicle; the z direction is vertical to the plane defined by the x and the y and points to the upper part of the ground; the position of the human thorax in the x, y and z directions is determined by the coordinates (px, py, pz) of the thorax in a cartesian rectangular coordinate system (x, y, z), the origin of which coincides with the projection of the position of the center of gravity of the vehicle on the ground at the moment of the human-vehicle collision.
3. The intelligent vehicle motion control method for protecting human-ground collision damage based on model predictive control according to claim 1, characterized in that: the estimation method of the human chest motion trajectory in step S2 is as follows:
assuming that the chest of the human body monitored in real time at the time t has the velocities vx0, vy0 and vz0 in the x, y and z directions and the positions px0, py0 and pz0, the chest positions of the human body at the time t +1 are as follows:
px1＝px0+vx0×Ts,
py1＝py0+vy0×Ts,
pz1＝pz0+vz0×Ts-g×Ts×Ts/2,
in the formula, g is the local gravity acceleration, Ts is the time step length, and the time step length is determined according to the sampling frequency of the intelligent vehicle monitoring equipment; and the motion trail of the chest of the human body within 10 time steps after the t moment can be obtained by calculating 10 times by analogy.
4. The intelligent vehicle motion control method for protecting human-ground collision damage based on model predictive control according to claim 1, characterized in that: in step S3, negative big finger e2< -0.5m, negative middle finger-0.5 m < e2< -0.3m, negative little finger-0.3 m < e2<0m, positive little finger 0m < e2<0.3m, middle finger 0.3m < e2<0.5m, and positive big finger e2>0.5 m.
5. The intelligent vehicle motion control method for protecting human-ground collision damage based on model predictive control according to claim 1, characterized in that: in step S4, the control rule of the movement of the vehicle in the x direction is: when e1 is positive, the vehicle is accelerated, and the acceleration value is 1m/s2(ii) a When e1 is negative, the vehicle is decelerated, and the acceleration value is taken as-1 m/s2(ii) a When e1 is zero, controlling the acceleration of the vehicle to be zero; in the process, when the vehicle detects that an obstacle or the positions of the head, the chest, the hip and the like of the human body in front are lower than the front edge of the engine hood, the motion control in the x direction is finished, and the vehicle is completely braked.
6. The intelligent vehicle motion control method for protecting human-ground collision damage based on model predictive control according to claim 1, characterized in that: in step S4, the motion control of the vehicle in the y direction includes:
s41: when the condition that e2 is not zero is monitored, a message is sent to the surrounding vehicles to give a clear lane change intention;
s42: when the people and the vehicle are separated from contact, the surrounding environment is monitored, and the transverse motion of the vehicle is controlled according to the following rules on the premise of confirming safety: if e2 is negative, setting the steering angle of the wheels to-15 degrees; if e2 is negative-medium, the steering angle of the wheels is set to-10 degrees; if e2 is negative, setting the steering angle of the wheels to be-5 degrees; if e2 is zero, setting the wheel steering angle to zero; if e2 is positive small, the wheel steering angle is set to 5 °; if e2 is in the middle, setting the steering angle of the wheels to 10 degrees; if e2 is positive, setting the wheel steering angle to 15 °; the vehicle steering angle is positive in the counterclockwise direction;
s43: and after the contact of the human and the vehicle is monitored, setting the steering angle of the wheels to be zero, and finishing the transverse motion control.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011519629.9A CN112606833B (en) | 2020-12-21 | 2020-12-21 | Model prediction control-based intelligent vehicle motion control method for protecting human-ground collision damage |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011519629.9A CN112606833B (en) | 2020-12-21 | 2020-12-21 | Model prediction control-based intelligent vehicle motion control method for protecting human-ground collision damage |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112606833A true CN112606833A (en) | 2021-04-06 |
| CN112606833B CN112606833B (en) | 2022-02-25 |
Family
ID=75243831
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011519629.9A Active CN112606833B (en) | 2020-12-21 | 2020-12-21 | Model prediction control-based intelligent vehicle motion control method for protecting human-ground collision damage |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112606833B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115675397A (en) * | 2022-11-11 | 2023-02-03 | 江苏天一航空工业股份有限公司 | Logistics luggage tractor line control power-assisted braking system and method |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005206103A (en) * | 2004-01-26 | 2005-08-04 | Mazda Motor Corp | Vehicular hood device |
| JP2008247111A (en) * | 2007-03-29 | 2008-10-16 | Fuji Heavy Ind Ltd | Collision safety control system for vehicle |
| CN104228754A (en) * | 2014-09-04 | 2014-12-24 | 浙江吉利控股集团有限公司 | Control method and control system of engine cover of vehicle |
| CN105774742A (en) * | 2013-08-09 | 2016-07-20 | 浙江吉利汽车研究院有限公司 | Safety system for automobile |
| JP2017065293A (en) * | 2015-09-28 | 2017-04-06 | ソニー株式会社 | Damage reduction device, damage reduction method, and program |
| CN109591755A (en) * | 2019-01-14 | 2019-04-09 | 长沙理工大学 | A kind of fast car protection people collsion damage method |
| CN110816465A (en) * | 2018-08-08 | 2020-02-21 | 本田技研工业株式会社 | Vehicle protection device |
| CN111497773A (en) * | 2019-01-30 | 2020-08-07 | 南京知行新能源汽车技术开发有限公司 | Vehicle safety protection system and method |
-
2020
- 2020-12-21 CN CN202011519629.9A patent/CN112606833B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005206103A (en) * | 2004-01-26 | 2005-08-04 | Mazda Motor Corp | Vehicular hood device |
| JP2008247111A (en) * | 2007-03-29 | 2008-10-16 | Fuji Heavy Ind Ltd | Collision safety control system for vehicle |
| CN105774742A (en) * | 2013-08-09 | 2016-07-20 | 浙江吉利汽车研究院有限公司 | Safety system for automobile |
| CN104228754A (en) * | 2014-09-04 | 2014-12-24 | 浙江吉利控股集团有限公司 | Control method and control system of engine cover of vehicle |
| JP2017065293A (en) * | 2015-09-28 | 2017-04-06 | ソニー株式会社 | Damage reduction device, damage reduction method, and program |
| CN110816465A (en) * | 2018-08-08 | 2020-02-21 | 本田技研工业株式会社 | Vehicle protection device |
| CN109591755A (en) * | 2019-01-14 | 2019-04-09 | 长沙理工大学 | A kind of fast car protection people collsion damage method |
| CN111497773A (en) * | 2019-01-30 | 2020-08-07 | 南京知行新能源汽车技术开发有限公司 | Vehicle safety protection system and method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115675397A (en) * | 2022-11-11 | 2023-02-03 | 江苏天一航空工业股份有限公司 | Logistics luggage tractor line control power-assisted braking system and method |
| CN115675397B (en) * | 2022-11-11 | 2023-11-24 | 江苏天一航空工业股份有限公司 | Logistics luggage tractor line-control power-assisted braking system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112606833B (en) | 2022-02-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11254307B2 (en) | Damage reduction device, damage reduction method, and program | |
| Wei et al. | A prediction-and cost function-based algorithm for robust autonomous freeway driving | |
| CN108062600A (en) | A kind of vehicle collision prewarning method and device based on rectangle modeling | |
| EP2759897B1 (en) | Method and arrangement for determining a trajectory | |
| CN112590871B (en) | Train safety protection method, device and system | |
| JP7234103B2 (en) | Vehicle control device and vehicle control system | |
| JP2016186683A (en) | Driving support device | |
| CN114442637A (en) | Unmanned vehicle local dynamic obstacle avoidance path planning method | |
| CN112606833B (en) | Model prediction control-based intelligent vehicle motion control method for protecting human-ground collision damage | |
| Matsumi et al. | Autonomous braking control system for pedestrian collision avoidance by using potential field | |
| CN111650945A (en) | Dynamic barrier anti-collision method | |
| CN106218612A (en) | A kind of method of vehicle safety travel, device and terminal | |
| CN112572378B (en) | Intelligent vehicle motion control method for protecting human-ground collision damage | |
| CN116601064A (en) | A method for controlling a vehicle when an obstacle is detected around the vehicle; control device for a vehicle having an autonomous driving function module; computer readable medium and motor vehicle | |
| CN112918470B (en) | Intelligent automatic emergency braking method for protecting pedestrians | |
| CN112918469B (en) | Automatic emergency braking system with active and passive safety function for pedestrians | |
| Matsumi et al. | Study on autonomous intelligent drive system based on potential field with hazard anticipation | |
| CN109754625A (en) | Take out the drive manner of vehicle in a kind of unpiloted campus | |
| CN115230685A (en) | Vehicle collision protection control method and advanced driving assistance system | |
| Hamid et al. | A safe-distance based threat assessment with geometrical based steering control for vehicle collision avoidance | |
| WO2017056375A1 (en) | Damage reduction device, damage reduction method, and program | |
| Brannstrom et al. | Threat assessment for avoiding collisions with turning vehicles | |
| CN113759933B (en) | Self-adaptive dynamic window track planning method for manned robot | |
| JP2006285925A (en) | Method and apparatus for reservation to avoid particle collision | |
| CN109147389B (en) | Method for planning route by autonomous automobile or auxiliary driving system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |