CN112026774B - Surrounding vehicle sideslip identification method based on own vehicle camera and radar sensing information - Google Patents

Surrounding vehicle sideslip identification method based on own vehicle camera and radar sensing information Download PDF

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CN112026774B
CN112026774B CN202010892719.6A CN202010892719A CN112026774B CN 112026774 B CN112026774 B CN 112026774B CN 202010892719 A CN202010892719 A CN 202010892719A CN 112026774 B CN112026774 B CN 112026774B
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vehicle
time
sideslip
surrounding
lane
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CN112026774A (en
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罗禹贡
向云丰
陈健
贺岩松
刘金鑫
王博
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Tsinghua University
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    • 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
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • 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
    • B60W40/02—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 ambient conditions
    • 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
    • B60W40/105—Speed
    • 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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles

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Abstract

The invention discloses a surrounding vehicle sideslip identification method based on a self-vehicle camera and radar sensing information, and belongs to the technical field of autonomous decision making of unmanned vehicles. The method is characterized in that the peripheral vehicle information and lane line equations acquired by a vehicle-mounted camera and a radar are used as known information, and a logic rule for judging whether the peripheral vehicle sideslips is formulated. Firstly, judging whether the suspected sideslip moment exists according to the track curvature of the surrounding vehicle, then judging whether the surrounding vehicle is closer to a lane line or not and whether the surrounding vehicle can quickly slide out of the lane line or not under the condition that the suspected sideslip moment exists, and finally judging whether the surrounding vehicle sideslips or not. According to the invention, the vehicle-mounted camera and the radar are used for acquiring the information of the surrounding vehicle and the lane line information, and the sideslip state of the surrounding vehicle is judged through the information, so that the problem that the existing unmanned vehicle cannot identify the sideslip state of the surrounding vehicle is solved, and a foundation is laid for the safe driving of the unmanned vehicle in the environment where the sideslip vehicle exists around.

Description

Surrounding vehicle sideslip identification method based on own vehicle camera and radar sensing information
Technical Field
The invention belongs to the technical field of autonomous decision making of unmanned automobiles, and particularly relates to a method for identifying a sideslip state of vehicles around an expressway, which helps the self-vehicle to better understand the state of the vehicles around the expressway and better perform behavior decision making and trajectory planning.
Background
Accurate understanding of the behavior of the surrounding vehicle and the vehicle running state by the unmanned vehicle is a precondition for safe running. At present, the behaviors of braking, lane changing, lane keeping, overtaking, steering and the like of surrounding vehicles can be well recognized by unmanned vehicles. The motion of a side-slipping vehicle is not easily controlled by the driver, and when the surrounding vehicle is side-slipping, it can pose a serious potential risk to the unmanned vehicle. In order to ensure road safety, the state (whether sideslip occurs or not) of the surrounding vehicles in the environment needs to be correctly identified according to information acquired by a vehicle sensor, so that the future tracks of the surrounding vehicles can be better predicted, and reasonable behavior decisions and track planning are made, thereby avoiding or reducing the influence of the surrounding sideslip vehicles on the vehicle.
In the prior art, a lane line equation, the distance from the edge of a surrounding vehicle to a lane line, the position and the speed of the surrounding vehicle and the state of a steering signal lamp of the surrounding vehicle can be obtained through a camera and a radar, and whether the self-vehicle sideslips or not is judged. However, no method for identifying the sideslip state of the surrounding vehicle based on the perception information of the unmanned vehicle exists at present.
Disclosure of Invention
The invention aims to provide an online sideslip identification method for an unmanned automobile on a highway facing to a surrounding running automobile in a mixed traffic flow. The invention judges whether the surrounding vehicle sideslips according to the information acquired by the vehicle-mounted sensor, and effectively solves the problem that the self vehicle is difficult to identify or monitor the sideslip state of the surrounding vehicle.
In order to achieve the purpose, the invention adopts the following technical scheme:
a peripheral vehicle sideslip identification method based on a self-vehicle camera and radar perception information specifically comprises 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 locatedl、lr(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 NNAnd a distance LNAnd 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 bicycleN(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 radarNAnd the position (x) of the surrounding vehicle in the three-dimensional world coordinate systemN，yN) The calculation formulas are respectively as follows:
VN＝vN+vsN
xN＝x0N+LN·cosαN
yN＝y0N+LN·sinαN
wherein, vsNThe current speed of the vehicle is the current speed of the vehicle; x is the number of0N，y0NThe longitudinal coordinates and the transverse coordinates of the self-vehicle at the current moment under a three-dimensional world coordinate system are obtained;
2) calculating the curvature radius of the vehicle track around the current time
Let TN，TN-1，TN-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，yN)，(xN-1，yN-1)，(xN-2，yN-2) (ii) a The radius of curvature ρ (N) of the vehicle trajectory around the current time N is determined using the following formula:
Figure GDA0003185289990000021
in the formula:
θ1Nand 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:
Figure GDA0003185289990000022
wherein lN-2，N-1、lN-1，NAnd lN-2，NRespectively the track points T of surrounding vehiclesN-2And TN-1、TN-1And TNAnd TN-2And TNThe calculation formula is as follows:
Figure GDA0003185289990000023
Figure GDA0003185289990000024
Figure GDA0003185289990000025
RNfor passing three track points T of surrounding vehicles simultaneouslyN，TN-1，TN-2The radius of the arc of (1), the center of the arc being ONFrom triangle ONTN-1TN-2The geometrical relationship of (a) yields:
Figure GDA0003185289990000026
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 stepCarving 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 closer and closer, if so, executing the step 10), otherwise, executing the step 7);
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 for the edge to reach the lane line is smaller than a sideslip time threshold value or not, and whether the distance from the edge to 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 k1Curvature of vehicle trajectory around timeThe radius is judged, whether the curvature radius of the vehicle track around the N moment is changed within a set range or not is judged, if the two conditions are met simultaneously, the step 9 is returned, and if the two conditions are not met simultaneously, the step 7 is returned);
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 steering lamp state information of the surrounding vehicle indicates lane change, judging whether the surrounding vehicle is in a normal lane change state or a sideslip state by combining the steering lamp state information: 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.
The invention has the following characteristics and beneficial effects:
the invention relates to a method for judging whether other vehicles sideslip or not based on self-vehicle perception information. The method comprises the steps of firstly acquiring the speed and the position of a surrounding vehicle and the state information of a steering lamp through a vehicle-mounted sensor, and acquiring a lane line equation and the distance from the edge of the surrounding vehicle to a lane line. And then, whether the peripheral vehicles sideslip or not is judged according to the acquired information, so that the problem that the existing unmanned vehicle cannot identify the sideslip state of the peripheral vehicles is solved, a foundation is laid for the safe driving of the unmanned vehicle in the environment with the existence of the sideslip vehicles around, and time is strived for the unmanned vehicle to avoid the risk.
Drawings
FIG. 1 is a schematic view of an unmanned vehicle driving scenario in which the method for identifying vehicle sideslip around the present invention is applied.
FIG. 2 is a block flow diagram of a method for identifying vehicle sideslip in the vicinity of the present invention.
FIG. 3 is a schematic diagram of the calculation of the curvature of the trajectory of the surrounding vehicle in the method for identifying side-slip of the surrounding vehicle of the present invention.
FIG. 4 is a schematic diagram of the relative positions of lane lines and vehicle trajectories in the method for identifying side-slip of a surrounding vehicle of the present invention.
FIG. 5 is a schematic illustration of a vehicle sideslip process in a surrounding vehicle sideslip identification method of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
For better understanding of the present invention, an application example of the present invention of a method for identifying the sideslip of the surrounding vehicle based on the camera of the vehicle and the radar perception information is described in detail below.
The invention discloses a surrounding sideslip vehicle identification method based on own vehicle cameras and radar perception information, application scenes and flow block diagrams of the method are respectively shown in fig. 1 and fig. 2, the method is explained for a certain surrounding vehicle, and other surrounding vehicles carry out sideslip identification according to the same method. The method comprises the following steps:
1) data acquisition through vehicle-mounted camera and radar
In the driving process of the self-vehicle, the vehicle-mounted camera and radar data are acquired through the CAN bus, wherein the information which CAN be acquired by the vehicle-mounted camera of the self-vehicle comprises: 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 locatedl、lr. The information that can be acquired by the vehicle-mounted radar of the own vehicle includes: speed v of vehicle relative to vehicle around current time NNAnd a distance LNAnd 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 bicycleN. Obtaining the speed V of the vehicle around the current moment according to the data obtained by the vehicle-mounted camera and the radarNAnd the position (x) of the surrounding vehicle in the three-dimensional world coordinate systemN，yN) The calculation formulas are respectively as follows:
VN＝vN+vsN
xN＝x0N+LN·cosαN
yN＝y0N+LN·sinαN
wherein, vsNThe current speed of the vehicle. x is the number of0N，y0NThe longitudinal coordinates and the transverse coordinates of the current time of the self-vehicle in a three-dimensional world coordinate system are shown. vs. vNAnd (x)N，yN) Are obtained according to the vehicle-mounted radar of the own vehicle and are known values.
2) Calculating the curvature radius of the vehicle track around the current time
Referring to FIG. 3, let TN，TN-1，TN-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，yN)，(xN-1，yN-1)，(xN-2，yN-2). The radius of curvature ρ (N) of the vehicle trajectory around the current time N is determined using the following formula:
Figure GDA0003185289990000051
in the formula:
θ1Nand 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:
Figure GDA0003185289990000052
wherein lN-2，N-1、lN-1，NAnd lN-2，NRespectively the track points T of surrounding vehiclesN-2And TN-1、TN-1And TNAnd TN-2And TNThe calculation formula is as follows:
Figure GDA0003185289990000053
Figure GDA0003185289990000054
Figure GDA0003185289990000055
RNfor passing three track points T of surrounding vehicles simultaneouslyN，TN-1，TN-2The radius of the arc of (a), the center of the arc being ONFrom triangle ONTN-1TN-2The geometrical relationship of (a) can be given by:
Figure GDA0003185289990000056
wherein, theta2NIs a line segment lN-2，NSubtended central angle, θ2N＝2(π-θ1N)。
Similarly, the curvature radius of each moment on the historical track of the surrounding vehicle can be obtained according to the method in the step 2).
3) And 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 any of the above conditions is not met, perform step 8). i and j are respectively the time k on the historical track of the surrounding vehicle1The previous and the next time. n is time k1The time within the previously set range is generally taken as the time k1First 0.2 s.
4) Judging time k1Until time N, whether the edge of the surrounding vehicle is closer to the lane line corresponding to the corresponding side of the surrounding vehicle, as shown by the dashed line in FIG. 1Shown in box 1.
If it satisfies lr(r1-1)≥lr(r1)，r1＝k1，k1+1, …, N, or satisfy ll(r1-1)≥ll(r1) If so, judging that the distance from the edge of the surrounding vehicle to the lane line on the corresponding side (left side or right side) is smaller and smaller, and executing the step 5); if the time k1The distance from the edge of the surrounding vehicle to the corresponding lane line on the corresponding side of the surrounding vehicle is closer and closer to the time N-1, the distance from the edge of the surrounding vehicle to the lane line begins to increase at the time N, and the current time k is recorded2I.e. k2N and then step 9) is performed. r is1Is time k1To the time between times N.
5) Judging whether the component of the current speed of the surrounding vehicle in the direction vertical to the lane of the surrounding vehicle is larger than a sideslip speed threshold value Yu or not1Whether 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 less than the sideslip time threshold Yu2Whether the distance from the edge of the current surrounding vehicle to the lane line where the surrounding vehicle is located is smaller than the sideslip distance threshold value Yu3) If the three conditions are not satisfied simultaneously, step 6) is executed, and if the three conditions are satisfied simultaneously, step 12) is executed. The method comprises the following specific steps:
referring to fig. 4, let the direction angle of the lane line of the lane where the vehicle is located around the current time be θ3NLet the speed direction angle of the vehicle around the current time be θ4NThe component V of the speed of the vehicle around the current time in the direction perpendicular to the laneTN＝VNsin(θ3N-θ4N). Assuming that the component of the speed of the surrounding vehicle in the direction perpendicular to the lane is constant before the left side or the right side slides out of the lane line, the time t when the surrounding vehicle reaches the left side or the right side lane line of the lane where the surrounding vehicle is located can be predictedpN：tpN＝dTN/VTN，dTNThe 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.
The selection of the three sideslip thresholds directly influences the emergency condition that the vehicle slides out of the lane line and the probability of sideslip misjudgment by the method. Wherein:
the component of the speed of the surrounding vehicle in a direction perpendicular to the lane in which the surrounding vehicle is located is related to the likelihood of whether a side slip is occurring. The greater the component of the surrounding vehicle speed in a direction perpendicular to the lane in which the surrounding vehicle is located, the greater the likelihood of sideslip. Side slip velocity threshold Yu1The value of (2) is reduced, so that the probability of missing recognition can be reduced, but the probability of false recognition can be increased. Yu1The value of (2) is increased, so that the probability of false recognition can be reduced, and meanwhile, the probability of missed recognition is increased. Preferably Yu1The value range of (a) is 0.1-1 m/s.
The time for the edge of the surrounding vehicle to reach the lane line of the lane where the surrounding vehicle is located represents an emergency situation in which the surrounding vehicle may slip out of the lane line corresponding to the surrounding vehicle. Side slip time threshold Yu2The value of (a) is reduced, the probability of false recognition can be reduced, but the time from recognizing that the surrounding vehicle sideslips to sliding out of the lane line of the surrounding vehicle by the system is reduced. Yu2The value of (a) is increased, the time from recognizing that the surrounding vehicle sideslips to the surrounding vehicle sliding out of the lane line can be increased, but the probability of false recognition can be increased. Preferably Yu2The value range of (a) is 0.5-1.5 s.
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 may slip out of the lane line corresponding to the surrounding vehicle. Sideslip distance threshold Yu3The value of (a) is reduced, the probability of false recognition can be reduced, but the time from recognizing that the surrounding vehicle sideslips to sliding out of the lane line of the surrounding vehicle by the system is reduced. Yu3The value of (a) is increased, the time from recognizing that the surrounding vehicle sideslips to the surrounding vehicle sliding out of the lane line can be increased, but the probability of false recognition can be increased. Preferably Yu3The value range of (a) is 0.2-0.8 m.
6) Calculating the curvature radius of the vehicle track around the next moment when the moment N is equal to N +1, and judging whether the curvature radius of the vehicle track around the moment 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, the step 4) is returned to, if notIf yes, step 7) is performed.
7) Determination time k1If not, step 8) is executed.
8) The curvature radius of the vehicle trajectory around the next time, i.e., the time N +1, is calculated, and the process returns to step 3).
9) And judging whether the distance from the peripheral vehicle edge to the lane line opposite to the lane line in the step 4) is closer and closer, as shown by a dotted line box 2 in fig. 1.
If it satisfies ll(r2-1)≥ll(r2)，r2＝k2，k2+1, …, N, or satisfy lr(r2-1)≥lr(r2) If so, judging that the distance from the edge of the surrounding vehicle to the left or right lane line is smaller and smaller, and executing step 10); otherwise step 7) is performed. r is2Is time k2Time to time between N.
10) Judging whether the component of the vehicle speed of the surrounding vehicle in the direction vertical to the lane at the moment N is larger than a sideslip speed threshold value Yu or not1Whether the time of the edge reaching the lane line is less than the sideslip time threshold value Yu2Whether the distance between the edge and the lane line is less than a sideslip distance threshold Yu3If the three conditions are not satisfied simultaneously, step 11) is executed, and if the three conditions are satisfied simultaneously, step 12) is executed.
11) Calculating the curvature radius of the vehicle track around the next moment when the moment N is equal to N +1, and judging whether the curvature radius of the vehicle track around the moment is less than k1And (3) judging whether the curvature radius of the vehicle track around the moment N is changed within a set range at the same time, returning to the step 9 if the two conditions are met at the same time, and returning to the step 7) if the two conditions are not met at the same time.
Referring to fig. 5, a vehicle that has sideslip tends to fluctuate within a certain range without a sudden decrease in curvature or a sudden increase in curvature. If the radius of curvature of the surrounding vehicle track satisfies | ρ (N) - ρ (p) | ≦ w ρ (N), p ═ N-q, N-q +1, …, N, the radius of curvature of the surrounding vehicle track fluctuates within a small range at time N. And w controls the fluctuation range of the curvature radius, and the value of w is suggested to be in the [0.0.2] interval.
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 time is the sideslip time. If the turn signal status information of the surrounding vehicle indicates lane change, it is necessary to determine whether the surrounding vehicle is in a normal lane change state or a sideslip state in combination with the turn signal status information.
If the turn light state information indicates that the lane is changed on the left side, when the vehicle drives through the lane line on the left side, the lane is judged to be changed normally, the lane is not sideslip, but the vehicle continuously slides out of the lane line on the left side or the lane line on the right side after the lane change is finished, and the vehicle is judged to sideslip. If the turn signal status information indicates that the lane is changed on the right, the determination process is similar.
When the peripheral vehicles in the same lane as the self-vehicle sideslip, if the peripheral vehicles do not slide out of the lane line in the same lane as the self-vehicle, the unmanned vehicle only needs to normally follow the vehicle, namely decelerate or stop; when the vehicles on other lanes slide laterally, if the vehicles do not slide out of the lane line of the lane, the vehicles do not influence the running of the unmanned vehicle. Only side-slipping vehicles sliding out of the lane line pose a threat to the safety of unmanned vehicles. The invention only identifies the sideslip vehicles which sideslip and finally slide out of the lane line.
The above is only a preferred embodiment of the present invention, it should be noted that the above embodiment does not limit the present invention, and various changes and modifications made by workers within the scope of the technical idea of the present invention fall within the protection scope of the present invention.

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, surrounding vehicleDistance l between the left and right edges and the left and right lane lines of the lane where the surrounding vehicle is locatedl、lr(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 NNAnd a distance LNAnd 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 bicycleN(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 radarNAnd the position (x) of the surrounding vehicle in the three-dimensional world coordinate systemN，yN) The calculation formulas are respectively as follows:
VN＝vN+vsN
xN＝x0N+LN·cosαN
yN＝y0N+LN·sinαN
wherein, vsNThe current speed of the vehicle is the current speed of the vehicle; x is the number of0N，y0NThe longitudinal coordinates and the transverse coordinates of the self-vehicle at the current moment under a three-dimensional world coordinate system are obtained;
2) calculating the curvature radius of the vehicle track around the current time
Let TN，TN-1，TN-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，yN)，(xN-1，yN-1)，(xN-2，yN-2) (ii) a The radius of curvature ρ (N) of the vehicle trajectory around the current time N is determined using the following formula:
Figure FDA0003185289980000011
in the formula:
θ1Nand 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:
Figure FDA0003185289980000012
wherein lN-2，N-1、lN-1，NAnd lN-2，NRespectively the track points T of surrounding vehiclesN-2And TN-1、TN-1And TNAnd TN-2And TNThe calculation formula is as follows:
Figure FDA0003185289980000013
Figure FDA0003185289980000014
Figure FDA0003185289980000015
RNfor passing three track points T of surrounding vehicles simultaneouslyN，TN-1，TN-2The radius of the arc of (1), the center of the arc being ONFrom triangle ONTN-1TN-2The geometrical relationship of (a) yields:
Figure FDA0003185289980000021
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 on the history track 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 the historical trajectories of the surrounding vehicles, respectivelyUpper time k1The 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 closer and closer, if so, executing the step 10), otherwise, executing the step 7);
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 k1Determining whether the peripheral vehicle sideslips or not by combining the state information of the steering lamps when the time is the heavy suspected sideslip time, and if the lane keeping indicated by the state information of the steering lamps of the peripheral vehicle is determined, determining k1The moment is the sideslip moment; if the steering lamp state information of the surrounding vehicle indicates lane change, judging whether the surrounding vehicle is in a normal lane change state or a sideslip state by combining the steering lamp state information: 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 theta3N，θ4NThe component V of the speed of the vehicle around the current time in the direction perpendicular to the laneTN＝VNsin(θ3N-θ4N) (ii) a If the component of the speed of the surrounding vehicle before sliding out of the lane line on the left side or the right side is unchanged in the direction vertical to the lane, the surrounding vehicle can be predicted to arrive at the left side or the right side lane of the lane where the surrounding vehicle is locatedTime t of linepN＝dTN/VTN，dTNThe 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 set range of the radius of curvature 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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