CN114394091B - Vehicle speed control method for traffic vehicles in adaptive cruise system under parallel road scene - Google Patents

Vehicle speed control method for traffic vehicles in adaptive cruise system under parallel road scene Download PDF

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CN114394091B
CN114394091B CN202210167005.8A CN202210167005A CN114394091B CN 114394091 B CN114394091 B CN 114394091B CN 202210167005 A CN202210167005 A CN 202210167005A CN 114394091 B CN114394091 B CN 114394091B
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vehicle
collision
ttc
corner
traffic
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CN114394091A (en
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赵健
刘彦辰
朱冰
宋东鉴
姜泓屹
孔德成
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Jilin University
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Jilin 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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0953—Predicting travel path or likelihood of collision the prediction being responsive to vehicle dynamic parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/14—Adaptive cruise control
    • B60W30/143—Speed control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/14—Adaptive cruise control
    • B60W30/16—Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18163—Lane change; Overtaking manoeuvres
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B60W2520/105—Longitudinal acceleration
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/14—Yaw
    • 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4042—Longitudinal 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4043—Lateral 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4044—Direction of movement, e.g. backwards
    • 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4045—Intention, e.g. lane change or imminent movement
    • 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/801—Lateral distance
    • 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/802—Longitudinal distance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The invention relates to a vehicle speed control method under a road merging scene of a traffic vehicle in a self-adaptive cruise system, which comprises the steps of collecting kinematic information of the traffic vehicle and adjacent traffic vehicles, identifying the road merging intention of the traffic vehicle in an adjacent lane, predicting the discrete track of the road merging traffic vehicle and the traffic vehicle, calculating the collision time, calculating the expected acceleration of the traffic vehicle and the like; the prediction capability of traffic situation in a long time is enhanced by considering the actual size of the vehicle to calculate the long time collision time and judge the collision situation; and calculating expected self-vehicle acceleration according to the collision time and the collision situation, controlling the vehicle to brake so as to pull away the following distance in advance, avoiding the collision risk, or accelerating so as to avoid the collision risk and improve the passing efficiency.

Description

Vehicle speed control method for traffic vehicles in adaptive cruise system under parallel road scene
Technical Field
The invention relates to a vehicle speed control method, in particular to a vehicle speed control method under a road merging scene of a traffic vehicle based on an adaptive cruise system.
Background
An automobile self-adaptive cruise system (ACC) detects the distance between a host vehicle and a front vehicle by using a sensor arranged on the automobile, and the ACC system sends instructions to a braking system and an engine control system according to the relative distance between the host vehicle and the front vehicle and the set speed of the automobile, so as to control the acceleration or the deceleration of the host vehicle and keep a safe distance with the front vehicle. The existing self-adaptive cruise system of the automobile mainly focuses on the distance control between the automobile and the automobile in front of the own lane, namely, the distance control between the automobile and the following object, but focuses on the automobile in the adjacent lane, when the automobile in the adjacent lane merges with the own lane, the automobile is set as the following object when half of the traffic automobile enters the own lane, the response of the automobile is delayed, and in order to increase the following distance to a safe distance in time, the situation of sudden braking occurs, and even accidents are likely to occur. The existing control methods for considering the lane merging condition of the traffic vehicles in advance do not consider specific side collision, rear-end collision and other collision modes when judging the vehicle interference condition, and lack of pre-reaction on the traffic vehicles merging to the own lane on the adjacent lanes, so that the prediction accuracy of collision time is required to be improved; when the vehicle speed is controlled, a conservative deceleration measure is adopted for the most part, and the passing efficiency is influenced.
Some existing adaptive cruise control methods focusing on the parallel line of a side-road vehicle still have the following problems: the specific track of the parallel line vehicle is not considered, the possible collision form is not considered, and the precision is to be improved; or the geometric model of the vehicle is assumed to be a point when judging whether the two vehicles interfere or not, the actual volume is not considered, the volume and the shape of the vehicle are not considered enough in the collision judgment, and the possible interference form between the vehicles cannot be fully considered.
Disclosure of Invention
The invention provides a vehicle speed control method under a parallel road scene of a traffic vehicle based on an adaptive cruise system, which aims to solve the technical problems existing in the existing adaptive cruise system and comprises the following steps:
the first step, collecting kinematic information of the own vehicle and the adjacent traffic vehicles: the method comprises the steps of speed, acceleration and yaw rate of the vehicle, and the transverse distance, longitudinal distance, course angle, yaw rate, longitudinal speed, transverse speed and the like of adjacent vehicles relative to the vehicle;
secondly, identifying the merging intention of the adjacent lane traffic vehicles: identifying the left lane change, the right lane change or the lane keeping intention of the adjacent lane traffic vehicles, and marking the traffic vehicles with the lane merging intention as the lane merging traffic vehicles;
thirdly, predicting discrete tracks of the parallel traffic vehicles and the self vehicles:
predicting a merging discrete track in future delta T time of the merging traffic vehicle: sampling frequency is f, and a parallel track discrete track sequence with the length of delta T multiplied by f is obtained, wherein the parallel track discrete track sequence comprises position, speed and orientation angle information of a parallel track traffic vehicle in future delta T time, and the parallel track discrete track sequence is converted into a vehicle coordinate system at the current moment;
predicting a discrete track within a future delta T time of the vehicle: the sampling frequency is f, namely a track sequence with the length of delta T multiplied by f is obtained, and the track sequence comprises the longitudinal position, the transverse position, the vehicle speed and the orientation angle information of the own vehicle relative to the current moment in the future delta T time;
fourth, calculating collision time:
short time collision time calculation: performing superposition detection on a predicted discrete track sequence by using a traversal method, and recording the moment corresponding to the track point which is superposed for the first time as collision time ttc;
if no coincidence occurs in the range of the predicted track in the rectangular frame coincidence detection, a uniform speed model is established, and further long-time collision time calculation and collision situation judgment are carried out;
fifthly, calculating the expected acceleration of the vehicle according to the collision time ttc and the collision situation obtained by calculation in the fourth step;
a sixth step, the automobile self-adaptive cruising system is communicated with the braking system and the driving system to generate proper braking pressure or engine output power, and the automobile is controlled to travel at expected acceleration until the self-adaptive cruising system is switched to a parallel traffic automobile or the longitudinal distance between the self-adaptive cruising system and the front automobile of the current lane is smaller than or equal to the following distance t after the following target is switched to the parallel traffic automobile h v h 。
Further, the fourth step of rectangular frame coincidence detection includes the following steps:
step 1, respectively calculating coordinates (x) of four corner points of a rectangular frame of a vehicle relative to track points of a parallel road traffic vehicle at the same moment through coordinate system conversion corner ,y corner ) fl,fr,rl,rr ；
Step 2, the corner coordinates (x) corner ,y corner ) fl,fr,rl,rr Long l of rectangular frame for parallel road traffic vehicle t Width w t Comparing, judging whether the corner of the rectangular frame of the own vehicle interferes with the parallel traffic vehicle, if the corner meets the following condition
Figure BDA0003516678040000031
And->
Figure BDA0003516678040000032
Indicating that the corner point collides with the traffic vehicle;
step 3, respectively calculating coordinates (x 'of four corner points of the rectangular frame of the parallel road traffic vehicle relative to the own vehicle track points at the same moment through coordinate system conversion' corner ,y' corner ) fl,fr,rl,rr ；
Step 4, corner coordinates (x 'of the parallel road traffic vehicle' corner ,y' corner ) fl,fr,rl,rr Length l of rectangular frame for bicycle h Width w h Comparing, judging whether the rectangular frame of the parallel road traffic vehicle has corner points to interfere with the own vehicle, if a certain corner point meets the requirement
Figure BDA0003516678040000033
And->
Figure BDA0003516678040000034
Indicating that the corner point collides with the vehicle;
step 5, referring to the steps 1 to 4, detecting the superposition condition of rectangular frames of the predicted track sequence by using a traversal method, wherein the index of the predicted track sequence, which is detected to be superposed with the rectangular frames at first, is k collision The collision time is recorded as ttc=k collision /f，ttc≤ΔT。
Further, the long-time collision time calculation and collision situation discrimination in the fourth step include the following steps:
step 1, extracting position, speed and orientation angle information of a self-vehicle and a parallel-road traffic vehicle when the final moment k=delta T×f of track prediction;
step 2, falseThe two are provided to keep constant-speed straight running,
Figure BDA0003516678040000035
for the course angle of the parallel-road traffic vehicle at the moment of k=delta T×f relative to the own vehicle at the same moment, v xk For the longitudinal relative speed of the parallel-road traffic vehicle and the own vehicle at the moment k=deltat×f, epsilon represents the normal fluctuation range of the course angle when the vehicle is in straight line running, if +.>
Figure BDA0003516678040000041
The collision situation and the collision time are calculated as follows:
collision situation is:
Figure BDA0003516678040000042
if it is
Figure BDA0003516678040000043
v xk Step 3, step 4, step 5 are performed below 0;
step 3,
Figure BDA0003516678040000044
v xk When less than 0, calculating longitudinal collision time ttc x And a side collision time ttc y The method comprises the steps of carrying out a first treatment on the surface of the The longitudinal and lateral collision time calculation method is shown as follows: />
Figure BDA0003516678040000045
Figure BDA0003516678040000046
Figure BDA0003516678040000047
Figure BDA0003516678040000048
Figure BDA0003516678040000049
Figure BDA00035166780400000410
Figure BDA00035166780400000411
In the above, x k 、y k 、v xk 、v yk The longitudinal relative distance, the transverse relative distance, the longitudinal relative speed and the transverse relative speed of the parallel road traffic vehicle and the own vehicle at the moment k=delta T×f respectively,
Figure BDA00035166780400000412
Figure BDA00035166780400000413
step 4, comparing the longitudinal side collision time with the group longitudinal side collision time, and determining the collision situation, wherein the method comprises the following steps:
if ttc x,1 ≥ttc y,1 If the collision situation I is the collision situation I, the vehicle head and the vehicle tail corner of the parallel traffic vehicle are in side-to-side diagonal collision;
if ttc x,2 ≥ttc y,2 &ttc x,1 ＜ttc y,1 If the collision situation II is the collision situation II, the corner of the vehicle head and the side edge of the parallel road traffic vehicle are collided in an angle-to-side manner;
if ttc x,3 ≥ttc y,3 &ttc x,2 ＜ttc y,2 If the collision situation III is the collision situation, the head corner of the parallel traffic vehicle collides with the side edge of the own vehicle in an angle-to-side manner;
if ttc x,4 ≥ttc y,4 &ttc x,3 ＜ttc y,3 Then, in case of a collision, IV,indicating that the head of the parallel road traffic vehicle collides with the vehicle corner at the tail of the vehicle diagonally;
step 5, calculating corresponding collision time ttc according to the determined collision situation, wherein a calculation formula is as follows:
collision case i:
Figure BDA0003516678040000051
crash situation ii:
Figure BDA0003516678040000052
/>
collision scenario iii:
Figure BDA0003516678040000053
collision scenario iv:
Figure BDA0003516678040000054
further, the method for calculating the expected acceleration of the own vehicle in the fifth step is as follows:
step 1, if ttc is less than or equal to deltaT or the judged collision situation is poor, I or II, the expected braking deceleration of the own vehicle is as follows:
Figure BDA0003516678040000055
step 2, if the determined collision situation is III or IV, no preceding vehicle exists in the current lane or the longitudinal distance x between the current lane and the preceding vehicle is the same follow ≥1.2t h v h The desired acceleration of the own vehicle is:
Figure BDA0003516678040000061
step 3, if the determined collision situation is III or IV, the current lane has a front car and the longitudinal distance x between the current lane and the front car follow ＜1.2t h v h The expected braking deceleration of the own vehicle is the same as that of the step 1;
wherein, a in the steps 1 to 3 bmax 、a amax Maximum braking acceleration and maximum acceleration, v, respectively, achievable by the vehicle h The speed t of the bicycle at the current moment h And setting a following time interval for the automobile self-adaptive cruise system.
The invention has the beneficial effects that:
compared with the prior art, the method fully considers the lane merging intention of the traffic vehicle and the possible specific running tracks of the own vehicle and the lane merging traffic vehicle in the future, and greatly improves the prediction precision of collision in a short time by detecting the superposition of rectangular frames and considering the actual size of the vehicle; further, long-time collision time calculation and collision situation judgment are performed by considering the actual size of the vehicle, so that the prediction capability of traffic situation in a long time is enhanced; in the prior art, the parallel-passage working conditions of most adjacent traffic vehicles can execute braking actions with different degrees, and the invention calculates expected self-vehicle acceleration according to collision time and collision situation, controls the vehicles to brake so as to pull the following distance away in advance, avoids collision risk, or accelerates so as to avoid collision risk and improve passing efficiency.
Drawings
Fig. 1 is an overall flow chart of the present invention.
FIG. 2 is a schematic diagram of the present invention for operating conditions.
Fig. 3 is a schematic diagram of short-time collision time and rectangular frame coincidence detection calculation according to the present invention.
Fig. 4 is a schematic diagram of a short-time collision time and rectangular frame coincidence detection calculation flow.
Fig. 5 is a schematic diagram of 4 kinds of collision situations in the long-term collision time calculation and collision situation discrimination according to the present invention.
Fig. 6 is a schematic diagram of a long-term collision time calculation and collision situation discrimination flow according to the present invention.
Fig. 7 is a schematic diagram of a calculation flow of the expected acceleration of the vehicle according to the present invention.
The labels in the figures are as follows:
1. the method comprises the following steps of self-vehicle, 2 parallel traffic vehicles, 3 front vehicles of the current lane, 4 four corner points of a rectangular frame of the self-vehicle, 5 four corner points of a rectangular frame of the parallel traffic vehicles.
Detailed Description
Please refer to fig. 1-7:
the invention provides a vehicle speed control method under a parallel road scene of a traffic vehicle based on an adaptive cruise system, which comprises the following steps:
s10, acquiring kinematic information of the own vehicle 1 and adjacent traffic vehicles: including the speed, acceleration, yaw rate of the host vehicle 1, lateral distance, longitudinal distance, heading angle, yaw rate, longitudinal speed, lateral speed, etc. of the adjacent vehicle relative to the host vehicle.
S20, identifying the merging intention of the adjacent lane traffic vehicles: the method comprises the following steps: training a hidden Markov model by utilizing the left lane change, right lane change and lane keeping data of the vehicle in the disclosed natural driving data set, and identifying the left lane change, right lane change or lane keeping intention of the adjacent lane traffic vehicle; the traffic vehicle having the intention to merge into the own lane is denoted as a merge traffic vehicle 2.
S30, predicting a merging discrete track in a future delta T time of the merging traffic vehicle 2: the track point is the position of the geometric center of the vehicle at the corresponding moment, the sampling frequency is f, the track sequence with the length of delta T multiplied by f is obtained, the track sequence comprises the position, the speed and the orientation angle information of the parallel road traffic vehicle 2 in the future delta T time, and the track sequence is converted into the own vehicle coordinate system at the current moment. The track prediction method comprises the following steps: and extracting track fragments of the left lane change and the right lane change of the vehicle by utilizing the disclosed vehicle lane change data in the natural driving data set, respectively training a lane change track prediction model of the left lane change and the right lane change of the vehicle by adopting a neural network, and obtaining a lane combination discrete track sequence of the traffic vehicle 2, wherein the prediction duration is delta T.
S40, predicting a discrete track in future delta T time of the vehicle 1: the track points are the positions of the geometric centers of the vehicle at corresponding moments, the sampling frequency is f, and the track sequence with the length of delta T multiplied by f is obtained and comprises the longitudinal position, the transverse position, the vehicle speed and the orientation angle information of the own vehicle 1 relative to the current moment in the future delta T time. The method comprises the following steps: according to the longitudinal speed and yaw rate of the vehicle 1 at the current moment, predicting the future track of the vehicle 1 by adopting a constant rotation rate and speed model, wherein a state transition equation is as follows:
Figure BDA0003516678040000081
state quantity x in k Represents the longitudinal position of the own vehicle at the moment k relative to the current moment y k Represents the transverse position of the own vehicle at the moment k relative to the current moment v k Indicating the speed of the own vehicle at time k,
Figure BDA0003516678040000082
indicating heading angle of own vehicle at time k relative to current time,/->
Figure BDA0003516678040000083
The angular velocity of the vehicle at the moment k is represented; Δt is the sampling step size.
S50, short-time collision time calculation: and (3) performing superposition detection on the predicted discrete track sequence by using a traversal method, namely, performing superposition detection on rectangular frames of the own vehicle 1 and the parallel road traffic vehicle 2, and recording the moment corresponding to the track point which is superposed for the first time as collision time ttc. The rectangular frame coincidence detection, as shown in fig. 1, 3 and 4, includes the following steps:
s51, respectively calculating coordinates (x) of four corner points of the rectangular frame of the own vehicle 1 relative to track points of the parallel road traffic vehicle 2 at the same moment through coordinate system conversion corner ,y corner ) fl,fr,rl,rr ；
S52, the corner coordinates (x) corner ,y corner ) fl,fr,rl,rr Long l of rectangular frame for parallel road traffic vehicle t Width w t Comparing, judging whether the rectangular frame of the own vehicle 1 has corner points to interfere with the parallel traffic vehicle 2, if a certain corner point meets the requirement
Figure BDA0003516678040000084
And->
Figure BDA0003516678040000085
Indicating that the corner point collides with the traffic vehicle;
s53, respectively calculating coordinates (x 'of four corner points of the rectangular frame of the parallel road traffic vehicle 2 relative to the track points of the own vehicle 1 at the same moment through coordinate system conversion' corner ,y' corner ) fl,fr,rl,rr ；
S54, corner coordinates (x 'of the parallel road traffic vehicle 2' corner ,y' corner ) fl,fr,rl,rr Length l of rectangular frame of bicycle 1 h Width w h Comparing, judging whether the rectangular frame of the parallel road traffic vehicle 2 has corner points to interfere with the own vehicle 1, if a certain corner point meets the requirement
Figure BDA0003516678040000091
And->
Figure BDA0003516678040000092
Indicating that the corner point collides with the vehicle;
s55, referring to S51-S54, detecting the superposition condition of rectangular frames of the predicted track sequence by using a traversal method, wherein the index of the predicted track sequence, which detects the superposition of the rectangular frames at first, is k collision The collision time is recorded as ttc=k collision /f，ttc≤ΔT。
S60, calculating long-time collision time and judging collision situations: if no coincidence occurs in the predicted track range in the S50 rectangular frame coincidence detection, a uniform velocity model is built to further predict collision time, as shown in fig. 1, 5 and 6, including the steps of:
s61, when the last time k=Δt×f of the track prediction is extracted, the position, speed, and direction angle information of the own vehicle 1 and the parallel road traffic vehicle 2;
s62 assuming that both travel straight at a constant speed,
Figure BDA0003516678040000093
for the course angle of the own vehicle 1 at the same time, v, of the parallel-road traffic vehicle 2 at the time of k=Δt×f xk For the longitudinal relative speed of the parallel-road traffic vehicle 2 and the own vehicle 1 at the moment k=Δt×f, ε represents the normal fluctuation range of the heading angle when the vehicle is traveling straight, and is a small positive real number, if + ∈ ->
Figure BDA0003516678040000094
v xk < 0, the collision situation and the collision time are calculated as follows:
collision situation is:
Figure BDA0003516678040000095
if it is
Figure BDA0003516678040000096
v xk < 0, executing S63, S64, S65;
S63、
Figure BDA0003516678040000097
v xk when less than 0, calculating longitudinal collision time ttc x And a side collision time ttc y The method comprises the steps of carrying out a first treatment on the surface of the The longitudinal and lateral collision time calculation method is shown as follows:
Figure BDA0003516678040000098
Figure BDA0003516678040000099
Figure BDA0003516678040000101
Figure BDA0003516678040000102
/>
Figure BDA0003516678040000103
Figure BDA0003516678040000104
Figure BDA0003516678040000105
in the above, x k 、y k 、v xk 、v yk The longitudinal relative distance, the transverse relative distance, the longitudinal relative speed and the transverse relative speed of the parallel road traffic vehicle 2 and the own vehicle 1 at the moment k=deltat×f respectively,
Figure BDA0003516678040000106
Figure BDA0003516678040000107
s64, comparing the longitudinal side collision time with the group longitudinal side collision time, and determining the collision situation, wherein the method comprises the following steps:
if ttc x,1 ≥ttc y,1 If the collision situation I is the collision situation I, the head of the own vehicle 1 and the tail corner of the parallel-road traffic vehicle 2 are collided diagonally;
if ttc x,2 ≥ttc y,2 &ttc x,1 ＜ttc y,1 If the collision situation II is the collision situation II, the head corner of the own vehicle 1 collides with the side edge of the parallel road traffic vehicle 2 in an angle-to-side manner;
if ttc x,3 ≥ttc y,3 &ttc x,2 ＜ttc y,2 If the collision situation III is shown, the head corner of the parallel road traffic vehicle 2 collides with the side edge of the own vehicle 1 in an angle-to-side manner;
if ttc x,4 ≥ttc y,4 &ttc x,3 ＜ttc y,3 If the collision situation IV is the collision situation IV, the head of the parallel road traffic vehicle 2 and the tail corner of the own vehicle 1 are collided diagonally;
s65, according to the collision situation determined in S64, calculating a corresponding collision time ttc, wherein the calculation formula is as follows:
collision case i:
Figure BDA0003516678040000108
crash situation ii:
Figure BDA0003516678040000111
collision scenario iii:
Figure BDA0003516678040000112
collision scenario iv:
Figure BDA0003516678040000113
s70, calculating the expected acceleration of the vehicle 1 according to the collision time ttc calculated in S50 and S60, wherein the method is as follows:
s71, if ttc is less than or equal to DeltaT or the collision condition judged by S60 is good, I or II, the expected braking deceleration of the bicycle 1 is as follows:
Figure BDA0003516678040000114
s72, if the collision condition determined in S60 is III or IV, no preceding vehicle is present in the current lane, or the longitudinal distance x from the preceding vehicle 3 in the current lane follow ≥1.2t h v h The desired acceleration of the vehicle is:
Figure BDA0003516678040000115
s73, if the collision situation determined in S60 is III or IV, the current lane has a preceding vehicle and is at a longitudinal distance x from the preceding vehicle 3 follow ＜1.2t h v h Self-propelled vehicleThe desired braking deceleration is the same as S71;
wherein a in S71 to S73 bmax 、a amax Maximum braking acceleration and maximum acceleration, v, respectively, achievable by the vehicle 1 h For the speed of the own vehicle 1 at the current moment, t h And setting a following time interval for the automobile self-adaptive cruise system.
S80, the automobile self-adaptive cruise system is communicated with the braking system and the driving system to generate proper braking pressure or engine output power, and the automobile is controlled to travel at expected acceleration until the self-adaptive cruise system is switched to the parallel road traffic automobile 2 along with the driving target or the longitudinal distance between the self-adaptive cruise system and the front automobile 3 of the current lane is smaller than or equal to the following distance t h v h 。

Claims (2)

1. A vehicle speed control method under a traffic vehicle parallel road scene in a self-adaptive cruise system is characterized in that: the method comprises the following steps:
the first step, collecting kinematic information of the own vehicle and the adjacent traffic vehicles: the method comprises the steps of speed, acceleration and yaw rate of the vehicle, and the transverse distance, longitudinal distance, course angle, yaw rate, longitudinal speed, transverse speed and the like of adjacent vehicles relative to the vehicle;
secondly, identifying the merging intention of the adjacent lane traffic vehicles: identifying the left lane change, the right lane change or the lane keeping intention of the adjacent lane traffic vehicles, and marking the traffic vehicles with the lane merging intention as the lane merging traffic vehicles;
thirdly, predicting discrete tracks of the parallel traffic vehicles and the self vehicles:
predicting a merging discrete track in future delta T time of the merging traffic vehicle: sampling frequency is f, and a parallel track discrete track sequence with the length of delta T multiplied by f is obtained, wherein the parallel track discrete track sequence comprises position, speed and orientation angle information of a parallel track traffic vehicle in future delta T time, and the parallel track discrete track sequence is converted into a vehicle coordinate system at the current moment;
predicting a discrete track within a future delta T time of the vehicle: the sampling frequency is f, namely a track sequence with the length of delta T multiplied by f is obtained, and the track sequence comprises the longitudinal position, the transverse position, the vehicle speed and the orientation angle information of the own vehicle relative to the current moment in the future delta T time;
fourth, calculating collision time:
short time collision time calculation: performing superposition detection on a predicted discrete track sequence by using a traversal method, and recording the moment corresponding to the track point which is superposed for the first time as collision time ttc;
if no coincidence occurs in the range of the predicted track in the rectangular frame coincidence detection, a uniform velocity model is established, and further long-time collision time calculation and collision situation judgment are carried out, and the method comprises the following steps:
step 1, extracting position, speed and orientation angle information of a self-vehicle and a parallel-road traffic vehicle when the final moment k=delta T×f of track prediction;
step 2, assuming that both travel straight at a constant speed,
Figure FDA0004216866690000011
for the course angle of the parallel-road traffic vehicle at the moment of k=delta T×f relative to the own vehicle at the same moment, v xk For the longitudinal relative speed of the parallel-road traffic vehicle and the own vehicle at the moment k=deltat×f, epsilon represents the normal fluctuation range of the course angle when the vehicle is in straight line running, if +.>
Figure FDA0004216866690000021
v xk < 0, the collision situation and the collision time are calculated as follows:
collision situation is:
Figure FDA0004216866690000022
if it is
Figure FDA0004216866690000023
v xk Step 3, step 4, step 5 are performed below 0;
step 3,
Figure FDA0004216866690000024
v xk When less than 0, calculating longitudinal collision time ttc x And a side collision time ttc y The method comprises the steps of carrying out a first treatment on the surface of the The longitudinal and lateral collision time calculation method is shown as follows:
Figure FDA0004216866690000025
Figure FDA0004216866690000026
Figure FDA0004216866690000027
/>
Figure FDA0004216866690000028
Figure FDA0004216866690000029
Figure FDA00042168666900000210
Figure FDA00042168666900000211
in the above, x k 、y k 、v xk 、v yk The longitudinal relative distance, the transverse relative distance, the longitudinal relative speed and the transverse relative speed of the parallel road traffic vehicle and the own vehicle at the moment k=delta T×f respectively,
Figure FDA00042168666900000212
Figure FDA00042168666900000213
step 4, comparing the longitudinal side collision time with the group longitudinal side collision time, and determining the collision situation, wherein the method comprises the following steps:
if ttc x,1 ≥ttc y,1 If the collision situation I is the collision situation I, the vehicle head and the vehicle tail corner of the parallel traffic vehicle are in side-to-side diagonal collision;
if ttc x,2 ≥ttc y,2 &ttc x,1 ＜ttc y,1 If the collision situation II is the collision situation II, the corner of the vehicle head and the side edge of the parallel road traffic vehicle are collided in an angle-to-side manner;
if ttc x,3 ≥ttc y,3 &ttc x,2 ＜ttc y,2 If the collision situation III is the collision situation, the head corner of the parallel traffic vehicle collides with the side edge of the own vehicle in an angle-to-side manner;
if ttc x,4 ≥ttc y,4 &ttc x,3 ＜ttc y,3 If the collision situation IV is the collision situation IV, the head of the parallel traffic vehicle and the corner of the tail of the vehicle are collided diagonally;
step 5, calculating corresponding collision time ttc according to the determined collision situation, wherein a calculation formula is as follows:
collision case i:
Figure FDA0004216866690000031
crash situation ii:
Figure FDA0004216866690000032
collision scenario iii:
Figure FDA0004216866690000033
collision scenario iv:
Figure FDA0004216866690000034
and fifthly, calculating the expected acceleration of the vehicle according to the collision time ttc and the collision situation obtained by calculation in the fourth step, wherein the method comprises the following steps:
step 1, if ttc is less than or equal to deltaT or the judged collision situation is poor, I or II, the expected braking deceleration of the own vehicle is as follows:
Figure FDA0004216866690000041
step 2, if the determined collision situation is III or IV, no preceding vehicle exists in the current lane or the longitudinal distance x between the current lane and the preceding vehicle is the same follow ≥1.2t h v h The desired acceleration of the own vehicle is:
Figure FDA0004216866690000042
step 3, if the determined collision situation is III or IV, the current lane has a front car and the longitudinal distance x between the current lane and the front car follow ＜1.2t h v h The expected braking deceleration of the own vehicle is the same as that of the step 1;
wherein, a in the steps 1 to 3 bmax 、a amax Maximum braking acceleration and maximum acceleration, v, respectively, achievable by the vehicle h The speed t of the bicycle at the current moment h The following time interval is set for the self-adaptive cruising system of the automobile;
a sixth step, the automobile self-adaptive cruising system is communicated with the braking system and the driving system to generate proper braking pressure or engine output power, and the automobile is controlled to travel at expected acceleration until the self-adaptive cruising system is switched to a parallel traffic automobile or the longitudinal distance between the self-adaptive cruising system and the front automobile of the current lane is smaller than or equal to the following distance t after the following target is switched to the parallel traffic automobile h v h 。
2. The method for controlling the speed of a vehicle in a parallel road scene of a traffic vehicle in an adaptive cruise system according to claim 1, wherein: the fourth step of rectangular frame coincidence detection comprises the following steps:
step 1, respectively calculating coordinates (x) of four corner points of a rectangular frame of a vehicle relative to track points of a parallel road traffic vehicle at the same moment through coordinate system conversion corner ,y corner ) fl,fr,rl,rr ；
Step 2, the corner coordinates (x) corner ,y corner ) fl,fr,rl,rr Long l of rectangular frame for parallel road traffic vehicle t Width w t Comparing, judging whether the corner of the rectangular frame of the own vehicle interferes with the parallel traffic vehicle, if the corner meets the following condition
Figure FDA0004216866690000043
And is also provided with
Figure FDA0004216866690000044
Indicating that the corner point collides with the traffic vehicle;
step 3, respectively calculating coordinates (x 'of four corner points of the rectangular frame of the parallel road traffic vehicle relative to the own vehicle track points at the same moment through coordinate system conversion' corner ,y' corner ) fl,fr,rl,rr ；
Step 4, corner coordinates (x 'of the parallel road traffic vehicle' corner ,y' corner ) fl,fr,rl,rr Length l of rectangular frame for bicycle h Width w h Comparing, judging whether the rectangular frame of the parallel road traffic vehicle has corner points to interfere with the own vehicle, if a certain corner point meets the requirement
Figure FDA0004216866690000051
And is also provided with
Figure FDA0004216866690000052
Indicating that the corner point collides with the vehicle;
step 5, referring to the steps 1 to 4, detecting the superposition condition of rectangular frames of the predicted track sequence by using a traversal method, and firstly detecting the predicted track sequence with the superposition of the rectangular framesColumn index k collision The collision time is recorded as ttc=k collision /f，ttc≤ΔT。
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