An automatic emergency steering control method considering driver comfort

Abstract

The application discloses an automatic emergency steering control method considering driver comfort, comprising the following steps: a vehicle-mounted sensor acquires ego vehicle information, a camera, a millimeter wave radar and an angular radar sensor acquire front three-lane dangerous target information; according to the dangerous target information, a dangerous target with minimum TTC, minimum relative longitudinal distance or minimum relative lateral distance is judged as a main dangerous target through arbitration, and information of the main dangerous target is output; according to the ego vehicle position, a path cluster is planned by combining a quintic polynomial and a scattering point method, and the optimal path is screened out through collision checking; according to the ego vehicle information, longitudinal speed planning is carried out, and an optimal longitudinal speed curve is planned; aiming at the optimal path, far and near preview points are adopted, a far point is processed by using a steady yaw angular velocity gain, a near point is processed by using PID control, and a final steering wheel turning angle is obtained through superposition; aiming at the optimal longitudinal speed planning curve, a feedforward and feedback combined method is adopted to calculate a final expected acceleration.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of vehicle steering control, and particularly relates to an automatic emergency steering control method considering driver comfort. BACKGROUND

[0002] The automatic emergency steering system belongs to the field of active safety auxiliary driving, and is generally based on the detection and identification functions of millimeter wave radar, a camera and an angle radar. When a dangerous target is detected and there is a risk of collision, the automatic emergency braking system cannot avoid the collision even if it decelerates and brakes. The vehicle prompts the driver to steer to avoid collision through sound, greatly reducing the risk of rear-end collision.

[0003] Through a large number of traffic accident studies, it is found that relying solely on emergency braking cannot avoid collision in some accident cases. When a pedestrian suddenly crosses the road in front of the vehicle during high-speed driving of the vehicle, the vehicle takes automatic emergency braking, and the rapid change of vehicle speed in a short time can reduce the risk of collision, but there is still a possibility of injuring the pedestrian. Current studies show that in these working conditions where emergency braking cannot avoid collision, the driver can still avoid collision by emergency steering, because the latest steering point of emergency steering is later than the latest braking point, thereby further reducing the risk of collision. Emergency steering often brings a large lateral acceleration, and under the premise of ensuring successful obstacle avoidance, how to reduce the discomfort of the driver will become the focus of future research. Most control strategies only consider the robustness and rapid response of control, without considering reducing the discomfort of the driver. SUMMARY

[0004] The purpose of the application is to provide an automatic emergency steering control method considering driver comfort, which reduces the lateral acceleration of emergency steering, ensures safe obstacle avoidance of the vehicle, and reduces the discomfort of the driver.

[0005] The technical solution of the application is:

[0006] An automatic emergency steering control method considering driver comfort, comprising the following steps:

[0007] Step (1): obtaining vehicle information through a vehicle-mounted sensor, including vehicle speed, vehicle lateral and longitudinal acceleration and other information;

[0008] Step (2): obtaining front left, middle and right lane dangerous vehicle information through a camera, millimeter wave radar and angle radar and other sensors;

[0009] Step (3): According to the left, middle and right three-lane dangerous vehicle information obtained in step (2), the dangerous target with the minimum TTC (time to collision), the minimum relative longitudinal distance or the minimum relative lateral distance is determined as the main dangerous target, and the speed, acceleration, relative longitudinal and lateral distance of the main dangerous target, and the trajectory point of the main dangerous target in a future certain time are output;

[0010] Step (4): According to the main dangerous target information obtained in step (3), the emergency steering path cluster is planned according to the position of the ego vehicle by combining the quintic polynomial and the scatter planning method, and it is judged whether the steering path collides with the main dangerous target by using the collision checking method, and the path with the most outer side curvature being relatively smooth is selected as the optimal path;

[0011] Step (5): Further, according to the current information of the ego vehicle, the longitudinal speed planning is added, and the speed cluster with the speed decreasing over time is designed, which is specifically divided into two parts:

[0012] The first part: the speed and acceleration information at the beginning and end of the speed planning are processed, and the highest speed is set as the initial speed, and the first speed curve has an acceleration condition, so the highest speed is processed, and the following formula is the highest speed and the lowest speed at the end of planning. According to the number of sampling curves, the speed interval is calculated, and a series of speeds at the end of planning are calculated by circulation:

[0013] v endmin =v start +TTC·a max ;

[0014] v endmax =v start +k·TTC·a max ;

[0015] In the formula, v endmin is the lowest speed at the end of planning, v endmax is the highest speed at the end of planning, v start is the initial speed at the beginning of planning, k is an adjustment coefficient, TTC is the time to collision, and a max is the maximum deceleration that the vehicle can achieve without side slipping.

[0016] The second part: the quartic polynomial is calculated, and the quartic polynomial is calculated according to the initial position, initial speed, initial acceleration, a series of end speed, end acceleration, and the specific solving process is as follows:

[0017] x=C0+C1·t+C2·t 2 +C3·t 3 +C4·t 4 ;

[0018] v = C1 + 2 · C2 · t + 3 · C3 · t 2 + 4 · C4 · t 3 ;

[0019] a = 2 · C2 + 6 · C3 · t + 12 · C4 · t 2 ;

[0020] Substitute the above information to solve the value of C0, C1, C2, C3 and C4:

[0021] C0 = x start ;

[0022] C1 = v start ;

[0023]

[0024]

[0025]

[0026] In the formula, x start is the initial position, v start is the initial velocity, a start is the initial acceleration, v endi is a series of terminal velocities, and a end is the terminal acceleration.

[0027] According to the collision checking method, the curve with smaller speed drop is selected as the optimal longitudinal velocity planning curve.

[0028] Step (6): Next, the optimal path of step (4) is subjected to lateral control;

[0029] For tracking of the optimal path, two pre-look points are selected in the optimal path, and the lateral distance deviation of the two points can be obtained by bringing the quintic polynomial of the optimal path into the quintic polynomial. The heading angle deviation can be obtained by deriving the quintic polynomial. The deviation at the far point is mainly processed by the steady-state yaw rate gain, and the deviation at the near point is processed by the PID control strategy. The two are superimposed to obtain the final steering wheel angle. The specific method is as follows:

[0030] 1) Calculate the curvature radius R at the far point:

[0031]

[0032] In the formula, R is the curvature radius at the far point, y far is the lateral distance deviation, and x far is the relative longitudinal distance.

[0033] Because the steady-state yaw rate gain formula is:

[0034]

[0035] where w r is the steady yaw rate, v x is the vehicle longitudinal speed, L is the wheelbase, δ is the front wheel steering angle, m is the vehicle mass, a is the distance from the front axle to the center of mass, b is the distance from the rear axle to the center of mass, k2 is the rear wheel cornering stiffness, and k1 is the front wheel cornering stiffness.

[0036] According to the above formula, the corresponding steering wheel angle θ far at the far point can be solved.

[0037]

[0038] where k is the front wheel steering angle to steering wheel angle coefficient, θ far is the steering wheel angle.

[0039] 2) Calculate the lateral speed error v error at the near point:

[0040] v error = k · x near - v x · sin θ loaclhead ;

[0041] where v error is the lateral speed error, k is the lateral distance deviation to lateral speed coefficient, and θ loaclhead is the heading angle deviation.

[0042] Next, using the PID control strategy, the lateral acceleration a lat at the near point is obtained:

[0043] a lat = k p · v error + k i · v error + k d · v error ;

[0044] Then the steering wheel angle θ near at the near point can be calculated:

[0045]

[0046] The final steering wheel angle is the superposition of the steering wheel angles at the far point and the near point θ last :

[0047] θ last = w1 · θ near + w2 · θ far ;

[0048] wherein w1 and w2 are weight coefficients of near point and far point.

[0049] Considering that directly using the superimposed steering wheel angle will cause excessive lateral acceleration, the driving experience of the driver will be very uncomfortable, so the weight coefficients w1 and w2 are allocated and adjusted.

[0050] The specific allocation basis is the vehicle speed, when the vehicle speed is higher, the corresponding far point weight coefficient w2 should be higher, that is, the preview is farther, and the steering wheel angle at the far point should be larger, and when the vehicle speed is lower, the corresponding near point weight coefficient w1 should be higher, that is, the preview is closer, and the steering wheel angle at the near point should be larger.

[0051] Step (7): Next, the optimal longitudinal speed planning curve of step (5) is subjected to longitudinal control.

[0052] The longitudinal control is specifically divided into two parts, one is the calculation of the feedforward part acceleration, and the other is the calculation of the feedback part expected acceleration.

[0053] (1) Feedforward acceleration calculation:

[0054] The calculation of the feedforward acceleration is obtained according to the driving resistance equation, and the specific formula is:

[0055] ∑F = F i +F w +F f +F j ;

[0056] wherein ∑F is the sum of resistance, F i is the slope resistance, F w is the air resistance, F f is the rolling resistance, and F j is the acceleration resistance:

[0057] F i = mgi;

[0058]

[0059] Ff = mgf;

[0060]

[0061] wherein i is the road slope, f is the rolling resistance coefficient, m is the total mass of the automobile (kg), g is the acceleration of gravity, 9.81 m / s 2 , C D is the air resistance coefficient; A is the windward area (m 2 ), v a is the vehicle speed (km / h), and δ is the automobile rotational mass conversion coefficient, is the driving acceleration.

[0062] The feedforward acceleration is calculated according to the sum of the driving resistances calculated above.

[0063]

[0064] wherein a feedforward is the feedforward acceleration, the sum of the four resistances is calculated above, and m is the vehicle mass.

[0065] (2) Desired acceleration calculation:

[0066] The desired acceleration is selected by PID control according to the error between the optimal longitudinal speed planning and the vehicle speed, and the final desired acceleration is obtained, as shown in the following formula:

[0067] a des = k p ·(v ref -v x ) + k i ·(v ref -v x ) + k d ·(v ref -v x );

[0068] The feedforward acceleration and the desired acceleration are added to obtain the final acceleration, which is sent to the controller together with the steering wheel angle obtained above, so that complete lateral and longitudinal control is achieved.

[0069] The advantages of the present application are:

[0070] The present application proposes an automatic emergency steering control method considering driver comfort, formulates a far and near point steering wheel angle distribution weight coefficient scheme, designs an optimal longitudinal speed planning method and establishes a mathematical expression. According to the actual situation, accurate distribution weight coefficients and appropriate longitudinal speed curves are selected, which can reduce the lateral acceleration of emergency steering, ensure the safety of vehicle obstacle avoidance, and also reduce the discomfort of the driver. BRIEF DESCRIPTION OF DRAWINGS

[0071] The present application will be further described below in combination with the drawings and embodiments:

[0072] Figure 1 is the flowchart of the automatic emergency steering control method of the present application. DETAILED DESCRIPTION

[0073] As Figure 1 shown, the automatic emergency steering control method considering driver comfort proposed by the present application includes the following steps:

[0074] S1: Obtain the ego vehicle information through the vehicle-mounted sensor, including the ego vehicle speed, ego vehicle lateral and longitudinal acceleration, etc.

[0075] S2: Obtain the front left, middle and right lane dangerous vehicle information through the camera, millimeter wave radar and angular radar sensors, etc.

[0076] S3: According to the left, middle and right lane dangerous vehicle information obtained in S2, arbitrate and determine the dangerous target with the minimum TTC (time to collision), the minimum relative longitudinal distance or the minimum relative lateral distance as the main dangerous target, and output the information such as the speed, acceleration, relative longitudinal and lateral distance of the main dangerous target, and the predicted trajectory points of the main dangerous target in the future;

[0077] S4: According to the main dangerous target information obtained in S3, combine the quintic polynomial and the scatter point planning method according to the position of the ego vehicle, plan to obtain the emergency steering path cluster, use the collision checking method to determine whether the steering path collides with the main dangerous target, and select the path with the most outer side curvature as the optimal path.

[0078] S5: According to the current information of the ego vehicle, add longitudinal speed planning, and design quartic polynomial speed cluster, which is specifically divided into two parts:

[0079] First part: Process the speed, acceleration, etc. at the beginning and end of the speed planning. Calculate the speed interval according to the number of sampling curves, and calculate a series of planned end point speeds in a loop:

[0080] v endmin =v start +TTC·a max ;

[0081] v endmax =v start +k·TTC·a max ;

[0082] In the formula, v endmin is the lowest speed at the planned end point, v endmax is the highest speed at the planned end point, v start is the initial speed at the beginning of the planning, k is the adjustment coefficient, TTC is the time to collision, and a max is the maximum deceleration that the vehicle can achieve without side slipping.

[0083] Second part: Calculate the quartic polynomial. According to the initial position, initial speed, initial acceleration, a series of end point speeds, and end point accelerations, calculate the quartic polynomial. The specific solving process is as follows:

[0084] x = C0 + C1 · t + C2 · t 2 + C3 · t 3 + C4 · t4 ;

[0085] v = C1 + 2 · C2 · t + 3 · C3 · t 2 + 4 · C4 · t 3 ;

[0086] a = 2 · C2 + 6 · C3 · t + 12 · C4 · t 2 ;

[0087] Substitute the above information to obtain the values of C0, C1, C2, C3 and C4.

[0088] C0 = x start ;

[0089] C1 = v start ;

[0090]

[0091]

[0092]

[0093] In the formula, x start is the initial position, v start is the initial speed, a start is the initial acceleration, v endi is a series of terminal speeds, and a end is the terminal acceleration.

[0094] Screen the curve with smaller speed drop as the optimal longitudinal speed planning curve.

[0095] S 6: For tracking the optimal path, select two far and near preview points in the optimal path, and bring them into the optimal path quintic polynomial to obtain the lateral distance deviation of the far and near points. Derive the quintic polynomial to obtain the heading angle deviation. The deviation at the far point is mainly processed by the steady-state yaw rate gain, and the deviation at the near point is processed by the PID control strategy. The two are superimposed to obtain the final steering wheel angle. The specific method is as follows:

[0096] 1) Calculate the curvature radius R at the far point:

[0097]

[0098] In the formula, R is the curvature radius at the far point, y far is the lateral distance deviation, and x far is the relative longitudinal distance.

[0099] The steady-state yaw rate gain formula is:

[0100]

[0101] where w r is the steady yaw rate, v x is the vehicle longitudinal speed, L is the wheelbase, δ is the front wheel steering angle, m is the vehicle mass, a is the distance from the front axle to the center of mass, b is the distance from the rear axle to the center of mass, k2 is the rear wheel cornering stiffness, and k1 is the front wheel cornering stiffness.

[0102] According to the above formula, the corresponding steering wheel angle θ far at the far point can be solved.

[0103]

[0104] where k is the front wheel steering angle to steering wheel angle coefficient, θ far is the steering wheel angle.

[0105] 2) Calculate the lateral velocity error v error at the near point:

[0106] v error = k · x near - v x · sin θ loaclhead

[0107] where v error is the lateral velocity error, k is the lateral distance deviation to lateral velocity coefficient, and θ loaclhead is the heading angle deviation.

[0108] Next, the PID control strategy is used to obtain the lateral acceleration a lat at the near point:

[0109] a lat = k p · v error + k i · v error + k d · v error

[0110] Then the steering wheel angle θ near at the near point can be calculated:

[0111]

[0112] The final steering wheel angle is obtained by superimposing the steering wheel angles at the far point and the near point θ last :

[0113] θ last = w1 · θ near + w2 · θ far

[0114] ​​​Wherein, w1 and w2 are weight coefficients of near point and far point.

[0115] The weight coefficients w1 and w2 are adjusted in consideration of the case that directly using the superimposed steering wheel angle leads to excessive lateral acceleration.

[0116] The specific allocation basis is the vehicle speed, when the vehicle speed is higher, the corresponding far point weight coefficient w2 should be higher, that is, the preview is farther, the steering wheel angle at the far point should be larger, when the vehicle speed is lower, the corresponding near point weight coefficient w1 should be higher, that is, the preview is closer, the steering wheel angle at the near point should be larger.

[0117] S 7: The longitudinal control is specifically divided into two parts, one is the calculation of the feedforward part acceleration, and the other is the calculation of the feedback part expected acceleration.

[0118] (1) Feedforward acceleration calculation:

[0119] The calculation of the feedforward acceleration is obtained according to the driving resistance equation, and the specific formula is:

[0120] ∑F = F i +F w +F f +F j ;

[0121] Wherein, ∑F is the sum of resistance, F i is the slope resistance, F w is the air resistance, F f is the rolling resistance, and F j is the acceleration resistance.

[0122] Fi = mgi;

[0123]

[0124] Ff = mgf;

[0125]

[0126] Wherein, i is the road slope, f is the rolling resistance coefficient, m is the total mass of the automobile (kg), g is the acceleration of gravity, 9.81 m / s2, CD is the air resistance coefficient; A is the windward area (m2), va is the vehicle speed (km / h), δ is the automobile rotating mass conversion coefficient, is the driving acceleration.

[0127] The feedforward acceleration is calculated according to the sum of the driving resistance calculated above.

[0128]

[0129] Wherein, afeedforward For feedforward acceleration, ∑F is the sum of the four resistances calculated above, m is the mass of the vehicle.

[0130] (2) Desired acceleration calculation:

[0131] The desired acceleration is selected by the PID control according to the error between the optimal longitudinal speed planning speed and the vehicle speed, and the final desired acceleration is obtained, which is specifically shown in the following formula:

[0132] a des = k p ·(v ref -v x ) + k i ·(v ref -v x ) + k d ·(v ref -v x );

[0133] The feedforward acceleration and the desired acceleration are added to obtain the final acceleration, which is sent to the controller at the same time as the steering wheel angle of S6, so that complete lateral and longitudinal control is realized.

[0134] According to the automatic emergency steering control method considering driver comfort provided by the application, the whole algorithm comprises three parts: collecting vehicle information, optimal path and optimal longitudinal speed curve planning, lateral path tracking control and longitudinal speed following control. First, the vehicle sensor collects the vehicle information and the dangerous target information, then the optimal path is planned based on the five-order polynomial and the optimal longitudinal speed curve is planned based on the four-order polynomial according to the vehicle information, finally, the lateral control strategy is designed to track the optimal path and the longitudinal control strategy is designed to follow the optimal longitudinal speed curve.

[0135] In summary, based on the automatic emergency steering system, in order to improve the driver comfort, the optimal longitudinal speed curve based on the four-order polynomial is provided, and the far and near point steering wheel angle distribution strategy is designed, so that the driver comfort is improved and the influence of the large lateral acceleration on the driver is reduced under the premise of ensuring the obstacle avoidance stability.

[0136] The above embodiments are only for illustrating the technical concept and characteristics of the application, the purpose is to enable those skilled in the art to understand the content of the application and implement it, and cannot limit the protection scope of the application. Any modification made according to the spirit and essence of the main technical solution of the application should be covered within the protection scope of the application.

Claims

1. An automatic emergency steering control method that takes driver comfort into account, characterized in that, Includes the following steps: Step (1): The vehicle-mounted sensors acquire vehicle information, including vehicle speed and lateral and longitudinal acceleration information; Step (2): Obtain information on dangerous vehicles in the left, middle and right lanes ahead using cameras, millimeter-wave radar and corner radar sensors; Step (3): Based on the dangerous vehicle information of the left, middle and right lanes obtained in step (2), the dangerous target with the smallest collision time, the smallest relative longitudinal distance or the smallest relative lateral distance is determined as the main dangerous target, and the information of the main dangerous target is output. Step (4): Based on the main dangerous target information obtained in step (3), and based on the vehicle position, combined with the planning method of fifth-order polynomial and point-spreading, an emergency turning path cluster is planned. The collision check method is used to determine whether the turning path collides with the main dangerous target, and the path with the smoothest outermost curvature is selected as the optimal path. Step (5): Based on the current information of the vehicle, add longitudinal speed planning, design a speed cluster that decreases with time, and select the curve with the smallest speed change as the optimal longitudinal speed curve; Step (6): Perform lateral path following control based on the optimal path obtained in step (4); Step (7): Perform longitudinal speed following control based on the optimal longitudinal speed curve obtained in step (5); The specific steps for planning the optimal longitudinal velocity curve in step (5) are as follows: Process the velocity and acceleration information at the beginning and end of the velocity planning process, calculate the velocity interval based on the number of sampled curves, and iteratively calculate to obtain a series of planned endpoint velocities: v endmin =v start +TTC·a max ; v endmax =v start +k·TTC·a max ; In the formula, v endmin To determine the minimum speed required to reach the destination, v endmax To determine the maximum speed at the destination, v start The initial velocity at the starting point of the plan is given by k, the adjustment coefficient is given by TTC, and the collision time is given by a. max The maximum deceleration that the vehicle can achieve without skidding; The fourth-order polynomial for calculating speed planning: x=C0+C1·t+C2·t 2 +C3·t 3 +C4·t 4 ; v=C1+2·C2·t+3·C3·t 2 +4·C4·t 3 ; a=2·C2+6·C3·t+12·C4·t 2 ; Substituting the initial position, initial velocity, initial acceleration, and a series of final velocities and accelerations, we can solve for the coefficients of the fourth-degree polynomial: C0=x start ; C1=v start ; In the formula, x start As the initial position, v start Let a be the initial velocity. start For the initial acceleration, v endi For a series of final velocities, a end The final acceleration; Based on the collision detection method, the curve with the smaller speed drop is selected as the optimal longitudinal speed planning curve.

2. The automatic emergency steering control method according to claim 1, characterized in that, The specific steps of the lateral path following control in step (6) are as follows: (1) Calculate the radius of curvature R at the far point: In the formula, R is the radius of curvature at the far point, and y far x represents the lateral distance deviation. far This refers to the relative longitudinal distance; Then, the steering wheel angle θ at the far point is calculated based on the steady-state yaw rate gain. far : In the formula, k is the coefficient from the front wheel steering angle to the steering wheel steering angle, and θ far Steering wheel angle; (2) Calculate the lateral velocity error v at the near point. error : v error =k·x near -v x ·shnθ loaclheead ; In the formula, v error The lateral velocity error is given by k, where k is the lateral distance deviation to the lateral velocity coefficient, and θ is the lateral velocity error. loaclhead This refers to the deviation in heading angle; The lateral acceleration 'a' at the near point is obtained using a PID control strategy. lat : a lat =k p ·v error +k i ·v error +k d ·v error ; Then the steering wheel angle θ at the nearest point can be calculated. near : The final steering wheel angle is obtained by superimposing the steering wheel angles at the far point and the near point. last : i last =w1·θ near +w2·θ far ; In the formula, w1 and w2 are the weight coefficients of the near point and the far point, respectively.

3. The automatic emergency steering control method according to claim 2, characterized in that, The weighting coefficients w1 and w2 are adjusted based on the vehicle's speed: the higher the vehicle's speed, the higher the corresponding far-point weighting coefficient w2 should be, that is, the farther the aiming is, the larger the steering wheel angle at the far point should be; the lower the vehicle's speed, the higher the corresponding near-point weighting coefficient w1 should be, that is, the closer the aiming is, the larger the steering wheel angle at the near point should be.

4. The automatic emergency steering control method according to claim 1, characterized in that, The specific steps of longitudinal speed following control in step (7) are as follows: (1) Calculate the feedforward acceleration: The feedforward acceleration is calculated based on the driving resistance equation, and the specific formula is as follows: ∑F=F i +F w +F f +F j ; In the formula, ∑F represents the sum of resistances, F i For slope resistance, F w For air resistance, F f For rolling resistance, F j For acceleration drag: F i =mgi; F f =mgf; In the formula, i is the road slope, f is the rolling resistance coefficient, m is the total mass of the vehicle (kg), g is the acceleration due to gravity, and C D A is the air resistance coefficient; A is the frontal area (m²). 2 ), v a Where is the vehicle speed (km / h), and δ is the vehicle rotational mass conversion factor. For driving acceleration; The feedforward acceleration is calculated based on the sum of the driving resistance calculated above: In the formula, a feedforward Let ∑F be the feedforward acceleration, ∑F be the sum of the four resistances calculated above, and m be the vehicle mass. (2) Calculate the desired acceleration: Based on the speed planned for optimal longitudinal velocity and the error between the vehicle's speed and the PID control, the final desired acceleration is obtained, as shown in the following formula: a des =k p ·(v ref -v x )+k i @(v ref -v x )+k d ·(v ref -v x ); The final acceleration is obtained by adding the feedforward acceleration and the desired acceleration.

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