CN112026774A - Surrounding vehicle sideslip identification method based on own vehicle camera and radar sensing information - Google Patents

Abstract

The invention discloses a method for identifying the sideslip of surrounding vehicles based on self-vehicle camera and radar perception information, and belongs to the technical field of autonomous decision-making of unmanned vehicles. Taking the surrounding vehicle information and lane line equation obtained by the on-board camera and radar as known information, the logic rules for judging whether the surrounding vehicles are skidding are formulated. First, judge whether there is a suspected side-slip moment according to the trajectory curvature of the surrounding vehicles, and then judge whether the surrounding vehicles are getting closer and closer to the lane line under the condition of the suspected side-slip moment, whether they will slide out of the lane line quickly, and finally determine whether the surrounding vehicles are Slip occurs. The invention uses the vehicle-mounted camera and radar to obtain the surrounding vehicle information and lane line information, and uses the information to discriminate the sideslip state of the surrounding vehicles. Driving a vehicle lays the groundwork for safe driving in environments with skidding vehicles around.

Description

Side-slip recognition method of surrounding vehicles based on self-vehicle camera and radar perception information

technical field

The invention belongs to the technical field of autonomous decision-making of unmanned vehicles, and in particular relates to a method for recognizing the sideslip state of vehicles around a highway, which helps the self-vehicle to better understand the state of surrounding vehicles, and to better perform behavioral decision-making and trajectory planning.

Background technique

An accurate understanding of the behavior of the surrounding vehicles and the driving state of the vehicle is a prerequisite for safe driving. At present, the braking, lane changing, lane keeping, overtaking, steering and other behaviors of surrounding vehicles can be better recognized by unmanned vehicles. The movement of the side-slipping vehicle is not easily controlled by the driver, and when the surrounding vehicles slip, it will bring serious potential risks to the unmanned vehicle. In order to ensure road safety, it is necessary to correctly identify the state of surrounding vehicles in the environment (whether it is side-slipping) based on the information obtained by the self-vehicle sensors, so as to better predict the future trajectory of surrounding vehicles and make reasonable behavioral decisions and trajectories. planning to avoid or reduce the impact of the surrounding vehicles on the vehicle.

The existing technology can obtain the lane line equation, the distance from the edge of the surrounding vehicle to the lane line, the position, speed and turn signal status of the surrounding vehicle through the camera and radar, and determine whether the vehicle is slipping. However, there is currently no method to identify the sideslip state of surrounding vehicles based on the perception information of unmanned vehicles.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide an online sideslip identification method for the unmanned vehicle on the highway facing the surrounding vehicles in the mixed traffic flow. According to the information obtained by the vehicle-mounted sensor, the present invention determines whether the surrounding vehicles are skidding, and effectively solves the problem that the self-vehicle is difficult to identify or monitor the sideslip state of the surrounding vehicles.

In order to achieve the above object, the present invention adopts the following technical solutions:

A method for identifying the sideslip of surrounding vehicles based on self-vehicle camera and radar perception information, which specifically includes the following steps:

1) Data acquisition through on-board camera and radar

During the driving process of the self-vehicle, the information obtained by the vehicle-mounted camera of the self-vehicle includes: the lane line equation, the status of the turn signal lights of the surrounding vehicles, and the distances l _l and l _r between the left and right edges of the surrounding vehicles and the left and right lane lines of the lane where the surrounding vehicles are located; During the driving process of the ego vehicle, the information obtained by the on-board radar of the ego car includes: the speed v _N and the distance L _N of the surrounding vehicles relative to the ego car at the current moment N, and the connection between the center of mass of the surrounding vehicles and the ego car and the center of the ego car. The included angle α _N of the axis; the speed V _N of the surrounding vehicles at the current moment and the position (x _N , y _N ) of the surrounding vehicles in the three-dimensional world coordinate system are obtained according to the data obtained by the on-board camera and the radar, and the calculation formulas are as follows:

V _N =v _N +vs _N

x _N =x _0N +L _N ·cosα _N

y _N =y _0N +L _N ·sinα _N

Among them, vs _N is the current speed of the vehicle; x _0N , y _0N are the horizontal and vertical coordinates of the vehicle at the current moment in the three-dimensional world coordinate system;

2) Calculate the curvature radius of the surrounding vehicle trajectory at the current moment

Let T _N , T _N-1 , T _N-2 be the current time N of the surrounding vehicle and the trajectory points corresponding to the previous two times N-1 and N-2, and their coordinates in the three-dimensional world coordinate system are (x _N ,y _N (,(x _N-1 ,y _N-1 ),(x _N-2 ,y _N-2 ); use the following formula to determine the radius of curvature ρ(N) of the vehicle trajectory around the current moment N:

where:

θ _1N is the included angle between time N-1 and the speed direction of the surrounding vehicles at time N, which is calculated according to the cosine law:

Among them, l _N-2,N-1 , l _N-1,N and l _N-2,N are the trajectory points T _N-2 and T _N-1 , T _N-1 and T _N and T of the surrounding vehicles, respectively The distance between _N-2 and T _N , the calculation formulas are as follows:

R _N is the arc radius passing through the three trajectory points T _N , T _N-1 , T _N-2 of the surrounding vehicles at the same time, obtained from the geometric relationship of the triangle O _N T _N-1 T _N-2 :

3) Determine whether there is a suspected side slip point according to the radius of curvature of the historical trajectory of the surrounding vehicles

If the radius of curvature of a certain moment k ₁ of the historical trajectory of the surrounding vehicles satisfies ρ(i-1)≤ρ(i), i=k ₁ -n,k ₁ -n+1,...,k ₁ , and ρ( k ₁ )≥ρ(j), j=k ₁ +1, k ₁ +2,...,N, then determine that the time k ₁ on the historical track of the surrounding vehicles is the suspected sideslip time, record the time k ₁ and execute Step 4); if not satisfied, then perform step 8); i and j are the moments before and after the time k ₁ on the historical track of the surrounding vehicles respectively; n is the time within the set range before the time k ₁ ;

4) Judging whether the distance between the edge of the surrounding vehicle and the lane line corresponding to the corresponding side of the surrounding vehicle between time _k1 and time N is getting closer and closer, if it is getting closer, then perform step ₅ ). Between time N-1, the distance between the edge of the surrounding vehicle and the lane line corresponding to the corresponding side of the surrounding vehicle is getting closer and closer, and the distance between the edge of the surrounding vehicle and the lane line becomes larger at time N, then the current time is recorded as k ₂ , that is, k ₂ =N, and then execute step 9);

5) Determine whether the component of the current speed of the surrounding vehicle in the direction perpendicular to the lane where the surrounding vehicle is located is greater than the sideslip speed threshold, and whether the time when the edge of the current surrounding vehicle reaches the lane line of the lane where the surrounding vehicle is located is less than the sideslip time threshold. Whether the distance from the edge of the surrounding vehicle to the lane line where the surrounding vehicle is located is less than the sideslip distance threshold, if the three conditions are not satisfied at the same time, perform step 6), if both are satisfied, perform step 12);

6) Calculate the radius of curvature of the trajectory of the surrounding vehicle at time N=N+1, and judge whether the radius of curvature of the trajectory of the surrounding vehicle at this time is less than the radius of curvature of the trajectory of the surrounding vehicle at time k ₁ , if so, continue to determine that time k ₁ is the moment of suspected sideslip , and return to step 4), if not, execute step 7);

7) Determine that time k ₁ is not a suspected slip time, and execute step 8);

8) Calculate the curvature radius of the vehicle trajectory around the time N=N+1, and return to step 3);

9) Determine whether the distance from the edge of the surrounding vehicles to the lane line opposite to the lane line in step 4) after time k ₂ is getting closer and closer, if it is getting closer, then execute step 10), if time k ₂ to time N-1 The distance between the surrounding vehicle edges and the lane line opposite to the lane line in step 4) is getting closer and closer, and the distance between the surrounding vehicle edges and the lane line becomes larger at time N, then step 7) is performed;

10) Determine whether the speed of the surrounding vehicles in the direction perpendicular to the lane at time N is greater than the sideslip speed threshold, whether the time for the edge to reach the lane line is less than the sideslip time threshold, and whether the distance between the edge and the lane line is less than the sideslip distance threshold. If the conditions are not satisfied at the same time, step 11) is performed, and if they are satisfied at the same time, step 12) is performed;

11) Calculate the radius of curvature of the trajectory of the surrounding vehicle at time N=N+1, determine whether the radius of curvature of the trajectory of the surrounding vehicle at this moment is less than the radius of curvature of the trajectory of the surrounding vehicle at time k ₁ , and at the same time judge whether the radius of curvature of the surrounding vehicle trajectory at time N is set Change within a certain range, if the two conditions are satisfied at the same time, then return to step 9), if not satisfied at the same time, then return to step 7);

12) Determine the moment k ₁ as the moment of severe suspected sideslip, and judge whether the surrounding vehicles are skidding in combination with the status information of the turn signal

If the lane indicated by the turn signal status information of the surrounding vehicles remains, it is determined that the time k ₁ is the moment of sideslip; if the turn signal status information of the surrounding vehicles indicates a lane change, it is judged that the surrounding vehicles are changing lanes normally in combination with the turn signal status information. Still in the state of sideslip: If the status information of the turn signal indicates a lane change, when the surrounding vehicles pass the corresponding lane line, it is determined as a normal lane change, not a sideslip, but if the surrounding vehicles continue to slide out after the lane change is completed Lane lines, it will be determined that the surrounding vehicles are slipping.

Features and beneficial effects of the present invention are as follows:

The present invention is a method for judging whether the other vehicle is skidding based on the perception information of the own vehicle. The invention first obtains the speed, position and turn signal status information of surrounding vehicles, the equation of lane line and the distance from the edge of the surrounding vehicle to the lane line through the vehicle-mounted sensor. Then, according to the obtained information, it is judged whether the surrounding vehicles are slipping, which solves the problem that the current unmanned vehicles cannot identify the side-slip state of the surrounding vehicles, and lays the foundation for the safe driving of the unmanned vehicles in the environment where there are side-slipping vehicles around. To build a foundation, buy time for driverless vehicles to avoid this risk.

Description of drawings

FIG. 1 is a schematic diagram of a driving scene of an unmanned vehicle to which the method for identifying the sideslip of surrounding vehicles of the present invention is applied.

FIG. 2 is a flow chart of the method for identifying the sideslip of surrounding vehicles according to the present invention.

FIG. 3 is a schematic diagram of the calculation of the curvature of the trajectory of the surrounding vehicles in the method for identifying the sideslip of the surrounding vehicles according to the present invention.

FIG. 4 is a schematic diagram of the relative positions of the lane line and the vehicle trajectory in the method for identifying the sideslip of a surrounding vehicle according to the present invention.

FIG. 5 is a schematic diagram of a vehicle sideslip process in the method for identifying the sideslip of surrounding vehicles according to the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and do not limit the protection scope of the present invention.

In order to better understand the present invention, an application example of the method for identifying the sideslip of surrounding vehicles based on the self-vehicle camera and radar perception information of the present invention is described in detail below.

A method for identifying a side-slipping vehicle based on the self-vehicle camera and radar perception information of the present invention, its application scene and flow chart are shown in Figure 1 and Figure 2 respectively. The method of the present invention is described below for a certain surrounding vehicle. Vehicles are identified by the same method for sideslip. The method of the present invention comprises the following steps:

1) Data acquisition through on-board camera and radar

During the driving process of the own vehicle, the on-board camera and radar data are obtained through the CAN bus. The information that can be obtained by using the on-board camera of the own vehicle includes: the lane line equation, the status of the turn signal lights of the surrounding vehicles, and the distance between the left and right edges of the surrounding vehicles. The distances l _l , l _r of the left and right lane lines of the lane. The information that can be obtained by the on-board radar of the own vehicle includes: the speed v _N and the distance L _N of the surrounding vehicles relative to the own vehicle at the current moment N, and the included angle α between the line connecting the center of mass of the surrounding vehicles and the center of mass of the own vehicle and the center axis of the own vehicle _N. According to the data obtained by the on-board camera and radar, the speed V _N of the surrounding vehicles at the current moment and the position (x _N , y _N ) of the surrounding vehicles in the three-dimensional world coordinate system are obtained. The calculation formulas are as follows:

V _N =v _N +vs _N

x _N =x _0N +L _N ·cosα _N

y _N =y _0N +L _N ·sinα _N

Among them, vs _N is the current speed of the vehicle. x _0N , y _0N are the horizontal and vertical coordinates of the vehicle at the current moment in the three-dimensional world coordinate system. Both vs _N and (x _N , y _N ) are obtained from the vehicle's on-board radar and are known values.

2) Calculate the curvature radius of the surrounding vehicle trajectory at the current moment

Referring to FIG. 3 , let T _N , T _N-1 , and T _N-2 be the trajectory points corresponding to the current moment N of the surrounding vehicle and its previous two moments N-1 and N-2, and its coordinates in the three-dimensional world coordinate system They are respectively (x _N , y _N ), (x _N-1 , y _N-1 ), (x _N-2 , y _N-2 ). Use the following formula to determine the radius of curvature ρ(N) of the vehicle trajectory around the current moment N:

where:

θ _1N is the included angle between time N-1 and the speed direction of the surrounding vehicles at time N, which is calculated according to the cosine law:

Among them, l _N-2,N-1 , l _N-1,N and l _N-2,N are the trajectory points T _N-2 and T _N-1 , T _N-1 and T _N and T of the surrounding vehicles, respectively The distance between _N-2 and T _N , the calculation formulas are as follows:

R _N is the radius of the arc that passes through the three trajectory points T _N , T N _{- 1} , T _{N - 2} of the surrounding vehicles at the same time. The circle of the arc is O _N . The geometric relationship can be obtained:

Wherein, θ _2N is the central angle subtended by the line segment l _N-2,N , and θ _2N =2(π-θ _1N ).

Similarly, according to the method described in step 2), the curvature radius at each moment on the historical trajectory of the surrounding vehicles can be obtained.

3) Determine whether there is a suspected side slip point according to the radius of curvature of the historical trajectory of the surrounding vehicles.

If the radius of curvature of a certain moment k ₁ of the historical trajectory of the surrounding vehicles satisfies ρ(i-1)≤ρ(i), i=k ₁ -n,k ₁ -n+1,...,k ₁ , and ρ( k ₁ )≥ρ(j), j=k ₁ +1, k ₁ +2,...,N, then determine that the time k ₁ on the historical track of the surrounding vehicles is the suspected sideslip time, record the time k ₁ and execute Step 4); if any one of the above conditions is not satisfied, perform step 8). i and j are the times before and after the time k ₁ on the historical trajectory of the surrounding vehicles, respectively. n is the time within the set range before time k ₁ , generally 0.2s before time k ₁ .

4) Determine whether the distance between the edge of the surrounding vehicle and the lane line corresponding to the corresponding side of the surrounding vehicle between time _k1 and time N is getting closer and closer, as shown by the dotted box 1 in FIG. 1 .

That is, if l _r (r ₁ -1)≥l _r (r ₁ ), r ₁ =k ₁ ,k ₁ +1,...,N, or if l _l (r ₁ -1)≥l _l (r ₁ ), then it is determined that the distance from the edge of the surrounding vehicle to the corresponding side (left or right) lane line is getting smaller and smaller, and step ₅ ) is executed; The distance of the lane line corresponding to the corresponding side is getting closer and closer, and the distance between the surrounding vehicle edge and the lane line starts to become larger at time N, record the current time as k ₂ , that is, k ₂ =N, and then execute step 9 ). r ₁ is the time between time k ₁ and time N.

5) Determine whether the component of the current speed of the surrounding vehicle in the direction perpendicular to the lane where the surrounding vehicle is located is greater than the sideslip speed threshold Yu ₁ , and whether the time when the edge of the current surrounding vehicle reaches the lane line of the lane where the surrounding vehicle is located is less than the sideslip time threshold. Yu ₂ , whether the distance from the edge of the current surrounding vehicle to the lane line where the surrounding vehicle is located is less than the sideslip distance threshold Yu ₃ ). Specific steps are as follows:

Referring to FIG. 4 , set the direction angle of the lane line of the lane where the surrounding vehicles are located at the current moment as θ _3N , and set the speed direction angle of the surrounding vehicles at the current moment as θ _4N , then the speed of the surrounding vehicles at the current moment is in the component V _TN perpendicular to the direction of the lane. =V _N sin(θ _3N −θ _4N ). Assuming that the component of the speed of the surrounding vehicles in the direction perpendicular to the lane is unchanged before the left or right slides out of the lane line, the time t _pN for the surrounding vehicles to reach the left or right lane line of the surrounding vehicle can be predicted: t _pN =d _TN /V _TN , where d _TN is the distance from the edge of the surrounding vehicle at the current moment to the left or right lane line of the lane where the surrounding vehicle is located.

The selection of the three sideslip thresholds directly affects the emergency situation of the vehicle sliding out of the lane line and the probability of misjudgment of sideslip by this method. in:

The component of the speed of a surrounding vehicle in a direction perpendicular to the lane in which the surrounding vehicle is located is related to the likelihood of slippage. The greater the component of the surrounding vehicle speed in the direction perpendicular to the lane where the surrounding vehicle is located, the greater the possibility of sideslip. Decreasing the value of the sideslip speed threshold Yu ₁ can reduce the probability of missed identification, but at the same time it will increase the probability of wrong identification. Increasing the value of Yu ₁ can reduce the probability of misidentification, but at the same time increase the probability of missed identification. Preferably, the value of Yu ₁ ranges from 0.1 to 1 m/s.

The time when the edge of the surrounding vehicle reaches the lane line of the lane where the surrounding vehicle is located represents an emergency situation in which the surrounding vehicle will slide out of the lane line corresponding to the surrounding vehicle. Decreasing the value of the sideslip time threshold Yu ₂ can reduce the probability of misrecognition, but at the same time reduce the time from when the system recognizes that the surrounding vehicle is sliding to the time when the surrounding vehicle slides out of the lane line. Increasing the value of Yu ₂ can increase the time from when the system recognizes that the surrounding vehicle slides to the time when the surrounding vehicle slides out of the lane line, but it will increase the probability of misrecognition. Preferably, the value range of Yu ₂ is 0.5-1.5s.

The distance from the edge of the surrounding vehicle to the lane line where the surrounding vehicle is located represents an emergency situation in which the surrounding vehicle will slide out of the lane line corresponding to the surrounding vehicle. Decreasing the value of the sideslip distance threshold Yu ₃ can reduce the probability of misrecognition, but at the same time reduce the time from when the system recognizes the surrounding vehicles side slipping to when the surrounding vehicles slip out of the lane line. Increasing the value of Yu ₃ can increase the time from when the system recognizes that the surrounding vehicle slides to the time when the surrounding vehicle slides out of the lane line, but it will increase the probability of misrecognition. Preferably, the value of Yu ₃ ranges from 0.2 to 0.8 m.

6) Calculate the time N=N+ ₁ , that is, the curvature radius of the surrounding vehicle trajectory at the next time, and judge whether the curvature radius of the surrounding vehicle trajectory at this time is less than the curvature radius of the surrounding vehicle trajectory at the k1 time, and if so, continue to determine the _k1 time as: If it is suspected to be slipping, go back to step 4), if not, go to step 7).

7) It is determined that the time k ₁ is not a suspected slip time, and step 8) is executed.

8) Calculate the time N=N+1, that is, the curvature radius of the surrounding vehicle trajectory at the next time, and return to step 3).

9) Determine whether the distance from the edge of the surrounding vehicle to the lane line opposite to the lane line in step 4) is getting closer, as shown in the dotted box 2 in FIG. 1 .

That is, if l _l (r ₂ -1)≥l _l (r ₂ ), r ₂ =k ₂ , k ₂ +1,...,N, or l _r (r ₂ -1)≥l _r (r ₂ ), then it is determined that the distance from the edge of the surrounding vehicle to the left or right lane line is getting smaller and smaller, and step ₁₀ ) is executed; The lane line is getting closer and closer, and at time N, the distance between the edge of the surrounding vehicle and the lane line begins to increase, then step 7) is performed. r ₂ is the time between time k ₂ and time N.

10) Determine whether the speed of the surrounding vehicles in the direction perpendicular to the lane at time N is greater than the sideslip speed threshold Yu ₁ , whether the time when the edge reaches the lane line is less than the sideslip time threshold Yu ₂ , and whether the distance between the edge and the lane line is less than the sideslip distance For the threshold Yu ₃ , if the three conditions are not satisfied at the same time, step 11) is performed, and if they are satisfied at the same time, step 12) is performed.

11) Calculate the time N=N+1, that is, the curvature radius of the surrounding vehicle trajectory at the next time, determine whether the curvature radius of the surrounding vehicle trajectory at this time is less than the curvature radius of the surrounding vehicle trajectory at time k ₁ , and judge the curvature of the surrounding vehicle trajectory at time N at the same time. Whether the radius changes within the set range, if both conditions are satisfied at the same time, return to step 9), if not, return to step 7).

Referring to Figure 5, the curvature of a vehicle after a side slip usually does not drop or increase suddenly, but fluctuates within a certain range. If the radius of curvature of the surrounding vehicle trajectory satisfies |ρ(N)-ρ(p)|≤wρ(N), p=N-q, N-q+1,...,N, then the radius of curvature of the surrounding vehicle trajectory at time N is fluctuate within a small range. w controls the fluctuation range of the radius of curvature, and it is recommended that w be within the range of [0.0.2].

12) Determine the moment k ₁ as the moment of severe suspected sideslip, and judge whether the surrounding vehicles are skidding in combination with the status information of the turn signal

If the lane indicated by the turn signal state information of the surrounding vehicles remains, it is determined that time k ₁ is the time of sideslip. If the turn signal status information of the surrounding vehicles indicates a lane change, it is necessary to combine the turn signal status information to determine whether the surrounding vehicles are changing lanes normally or in a side-slip state.

If the status information of the turn signal indicates a left lane change, when the vehicle passes the left lane line, it is determined to be a normal lane change, not a sideslip, but the vehicle will continue to slide out of the left lane line or the right side after the lane change is completed. The lane markings will determine that the vehicle is slipping. If the turn signal status information indicates a right lane change, the determination process is similar.

When a surrounding vehicle in the same lane as the vehicle slips, if it does not slip out of the lane line in the same lane as the vehicle, the unmanned vehicle only needs to follow the vehicle normally to slow down or stop; The vehicle slides sideways, if it does not slide out of the lane line of the lane, it will not affect the driving of the driverless vehicle. Therefore, only the side-slipping vehicle that slips out of the lane line will pose a threat to the safety of the unmanned vehicle. The present invention only recognizes the side-slipping vehicle that has a side-slip and will eventually slip out of the lane line.

The above are only the preferred embodiments of the present invention. It should be noted that the above embodiments do not limit the present invention. Various changes and modifications made by the relevant staff within the scope of not departing from the technical idea of the present invention are all within the protection of the present invention. within the range.

Claims (6)

1. A peripheral vehicle sideslip identification method based on a self-vehicle camera and radar perception information is characterized by comprising the following steps:

1) data acquisition through vehicle-mounted camera and radar

In the driving process of the self-vehicle, the information acquired by utilizing the vehicle-mounted camera of the self-vehicle comprises the following steps: lane line equation, surrounding vehicle turn signal light state, distance l between left and right edges of surrounding vehicle and left and right lane lines of lane where the surrounding vehicle is located_l、l_r(ii) a In the driving process of the self-vehicle, the information acquired by utilizing the vehicle-mounted radar of the self-vehicle comprises the following steps: speed v of vehicle relative to vehicle around current time N_NAnd a distance L_NAnd an included angle alpha between a connecting line of the center of mass of the surrounding vehicle and the center of mass of the bicycle and the central axis of the bicycle_N(ii) a Obtaining the speed V of the vehicle around the current moment according to the data obtained by the vehicle-mounted camera and the radar_NAnd the position (x) of the surrounding vehicle in the three-dimensional world coordinate system_N,y_N) The calculation formulas are respectively as follows:

V_N＝v_N+vs_N

x_N＝v_0N+L_N·cosα_N

y_N＝y_0N+L_N·sinα_N

wherein, vs_NThe current speed of the vehicle is the current speed of the vehicle; x is the number of_0N,y_0NThe horizontal coordinate and the vertical coordinate of the current time of the self-vehicle under a three-dimensional world coordinate system are shown;

2) calculating the curvature radius of the vehicle track around the current time

Let T_N,T_N-1,T_N-2The coordinates of the track points corresponding to the current moment N and the previous two moments N-1 and N-2 of the surrounding vehicles under the three-dimensional world coordinate system are respectively (x)_N,y_N),(x_N-1,y_N-1),(x_N-2,y_N-2) (ii) a The radius of curvature ρ (N) of the vehicle trajectory around the current time N is determined using the following formula:

in the formula:

θ_1Nand calculating an included angle between the speed directions of the vehicles around the N-1 moment and the N moment according to the cosine law to obtain:

wherein l_N-2,N-1、l_N-1,NAnd l_N-2,NRespectively the track points T of surrounding vehicles_N-2And T_N-1、T_N-1And T_NAnd T_N-2And T_NThe calculation formula is as follows:

R_Nfor passing three track points T of surrounding vehicles simultaneously_N,T_N-1,T_N-2Radius of arc of (1), formed by triangle O_NT_N-1T_N-2The geometrical relationship of (a) yields:

3) judging whether a suspected sideslip point exists according to the curvature radius of the historical track of the surrounding vehicle

If the historical track of the surrounding vehicle at a certain moment k₁The radius of curvature of (a) satisfies rho (i-1) rho (i), i ═ k₁-n,k₁-n+1,…,k₁And satisfies ρ (k)₁)≥ρ(j)，j＝k₁+1,k₁+2, …, N ", the time k at which the historical trajectory of the surrounding vehicle is determined₁Recording the time k for the suspected sideslip time₁And performing step 4); if not, executing step 8); i and j are respectively the time k on the historical track of the surrounding vehicle₁The time of day before and after; n is time k₁The time within the previously set range;

4) judging time k₁Until the time N, whether the peripheral vehicle edge is closer to the lane line corresponding to the corresponding side of the peripheral vehicle, if so, executing the step 5), and if so, executing the step k₁Until the time N-1, the distance between the edge of the surrounding vehicle and the corresponding lane line of the corresponding side of the surrounding vehicle is closer and closer, and the distance between the edge of the surrounding vehicle and the lane line at the time N begins to increase, then the current time k is recorded₂I.e. k₂N, and then step 9) is performed;

5) judging whether the component of the current speed of the surrounding vehicle in the direction vertical to the lane where the surrounding vehicle is located is larger than a sideslip speed threshold value, whether the time for the edge of the current surrounding vehicle to reach the lane line of the lane where the surrounding vehicle is located is smaller than a sideslip time threshold value, and whether the distance from the edge of the current surrounding vehicle to the lane line where the surrounding vehicle is located is smaller than a sideslip distance threshold value, if the three conditions are not met simultaneously, executing the step 6), and if the three conditions are met simultaneously, executing the step 12);

6) calculating the curvature radius of the vehicle track around the time N +1, and judging whether the curvature radius of the vehicle track around the time is less than k₁If the curvature radius of the vehicle track around the time is the same, continuing to determine k₁The time is the suspected sideslip time, and the step 4) is returned, if not, the step 7) is executed;

7) determination time k₁If not, executing step 8);

8) calculating the curvature radius of the vehicle track around the time N +1, and returning to the step 3);

9) judging time k₂Then, whether the distance from the peripheral vehicle edge to the lane line opposite to the lane line in the step 4) is more and more advanced or not is judged, if so, the step 10) is executed, and if the time k is more and more₂Until the time N-1, the distance between the peripheral vehicle edge and the lane line opposite to the lane line in the step 4) is closer and closer, and the distance between the peripheral vehicle edge and the lane line at the time N starts to be larger, then the step 7) is executed;

10) judging whether the component of the speed of the vehicle around the N moment in the direction vertical to the lane is larger than a sideslip speed threshold value or not, whether the time of the edge reaching the lane line is smaller than a sideslip time threshold value or not, and whether the distance of the edge from the lane line is smaller than a sideslip distance threshold value or not, if the three conditions are not met simultaneously, executing the step 11), and if the three conditions are met simultaneously, executing the step 12);

11) calculating the curvature radius of the vehicle track around the time N +1, and judging whether the curvature radius of the vehicle track around the time is less than k₁Judging whether the curvature radius of the vehicle track around the moment N is changed within a set range, if the two conditions are met, returning to the step 9), and if the two conditions are not met, returning to the step 7);

12) determination k₁The moment is the severe suspected sideslip moment, and whether the surrounding vehicle sideslips or not is judged by combining the state information of the steering lamp

If the lane keeping indicated by the turn signal state information of the surrounding vehicle is detected, k is determined₁The moment is the sideslip moment; if the state information of the turn lights of the surrounding vehiclesAnd if the lane change is shown, judging whether the surrounding vehicle is in a normal lane change state or a sideslip state by combining the state information of the steering lamp: if the state information of the steering lamps indicates lane changing, when surrounding vehicles drive through corresponding lane lines, the lane changing is determined to be normal and not sideslip, but after the lane changing is completed, if the surrounding vehicles continuously slide out of the lane lines, the surrounding vehicles are determined to sideslip.

2. The peripheral vehicle sideslip identification method according to claim 1, characterized in that in step 5), the component of the current speed of the peripheral vehicle in the direction perpendicular to the lane where the peripheral vehicle is located, the time when the edge of the current peripheral vehicle reaches the lane line of the lane where the peripheral vehicle is located, and the distance from the edge of the current peripheral vehicle to the lane line where the peripheral vehicle is located are calculated as follows:

setting the direction angle and the speed direction angle of a lane line of a lane where a vehicle is located around the current time as theta_3N,θ_4NThe component V of the speed of the vehicle around the current time in the direction perpendicular to the lane_TN＝V_Nsin(θ_3N-θ_4N) (ii) a The component of the speed of the surrounding vehicle before sliding out of the lane line on the left side or the right side in the direction vertical to the lane line is not changed, so that the time t when the surrounding vehicle reaches the lane line on the left side or the right side of the lane where the surrounding vehicle is located can be predicted_pN＝d_TN/V_TN，d_TNThe distance from the edge of the surrounding vehicle to the left or right lane line of the lane where the surrounding vehicle is located at the current moment.

3. The peripheral vehicle sideslip identification method according to claim 1, characterized in that in step 11), the fluctuation range of the curvature radius of the peripheral vehicle trajectory at time N is controlled to be between [0,0.2 ].

4. The peripheral vehicle sideslip identification method of claim 1, characterized in that the sideslip velocity threshold value ranges from 0.1 to 1 m/s.

5. The peripheral vehicle sideslip identification method of claim 1, characterized in that the sideslip time threshold value ranges from 0.5 s to 1.5 s.

6. The peripheral vehicle sideslip identification method according to claim 1, characterized in that the sideslip distance threshold value ranges from 0.2 m to 0.8 m.

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