CN110816526A - Acceleration control method and device for automatically driving vehicle to avoid threat and storage medium - Google Patents
Acceleration control method and device for automatically driving vehicle to avoid threat and storage medium Download PDFInfo
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- 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
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- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
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- B60W2554/80—Spatial relation or speed relative to objects
- B60W2554/802—Longitudinal distance
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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
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Abstract
The invention relates to a method, a device and a storage medium for controlling an automatic driving vehicle to avoid threat acceleration.A sensing module acquires the running information of the vehicle in front of a lane where the automatic driving vehicle is located and the running information of the vehicles in other lanes; the prediction module predicts the vehicle running tracks of other lanes and predicts the cut-in vehicle running information before the lane where the automatic driving vehicle is located; the control module calculates the rear-end collision prevention acceleration a0 required by the automatic driving vehicle according to the running information of the vehicle in front of the lane where the automatic driving vehicle is located; and calculating a cut-in threat escape acceleration aq required by the automatic driving vehicle according to the predicted forward cut-in vehicle running information, and taking the minimum value of the rear-end collision preventing acceleration a0 and the cut-in threat escape acceleration aq as the current required acceleration of the automatic driving vehicle. The invention can avoid cutting into the vehicle from the front cut in other lanes, and effectively avoid the risk of collision between the automatic driving vehicle and the front vehicle.
Description
Technical Field
The invention relates to an acceleration control method, device and storage medium for automatically driving a vehicle to avoid threats.
Background
In recent years, with the development of science and technology, especially the rapid development of intelligent computing, the research of the automatic driving automobile technology becomes a focus of all industries. The '12 leading edge technologies for determining future economy' report issued by McKensin discusses the influence degree of the 12 leading edge technologies on the future economy and society, and analyzes and estimates the respective economic and social influence of the 12 technologies in 2025, wherein the automatic driving automobile technology is ranked at the 6 th position, and the influence of the automatic driving automobile technology in 2025 is estimated as follows: economic benefits are about $ 0.2-1.9 trillion per year, and social benefits can recover 3-15 million lives per year.
According to the technical field division, the automatic driving can be divided into a sensing module, a positioning module, a prediction module, a control module and an execution module. The sensing module is equivalent to eyes of people, the peripheral environment state is collected in real time through sensors such as a camera, a millimeter wave radar and a laser radar, the positioning module is used for obtaining position information of the vehicle, the prediction module is used for predicting the self running track of the vehicle or predicting the track of other vehicles, pedestrians and motor vehicles, the control is decision and planning of vehicle motion, and the execution is a decision planning command of executing the vehicle.
In the prior art, most of prediction modules of automatic driving vehicles only predict the track of the vehicle, but do not predict the running tracks of other vehicles. Correspondingly, when the automatic driving vehicle runs in the lane, the rear-end collision prevention safety control is only carried out on the vehicle in front of the lane where the automatic driving vehicle is located, the rear-end collision prevention safety control is not carried out on the vehicles suddenly cut into other lanes, and the potential danger of collision exists.
Disclosure of Invention
The invention aims to provide an acceleration control method, device and storage medium for avoiding threat of an automatic driving vehicle, which can avoid a front cut-in vehicle cut-in from other lanes and effectively avoid the risk of collision between the automatic driving vehicle and the front vehicle.
Based on the same inventive concept, the invention has three independent technical schemes:
1. a control method for avoiding threat acceleration of an automatic driving vehicle is characterized by comprising the following steps:
the method comprises the steps that a sensing module obtains vehicle running information in front of a lane where an automatic driving vehicle is located and vehicle running information of other lanes;
the prediction module predicts the vehicle running tracks of other lanes and predicts the cut-in vehicle running information before the lane where the automatic driving vehicle is located;
the control module calculates the rear-end collision prevention acceleration a0 required by the automatic driving vehicle according to the running information of the vehicle in front of the lane where the automatic driving vehicle is located; and calculating a cut-in threat escape acceleration aq required by the automatic driving vehicle according to the predicted forward cut-in vehicle running information, and taking the minimum value of the rear-end collision preventing acceleration a0 and the cut-in threat escape acceleration aq as the current required acceleration of the automatic driving vehicle.
Further, when s 1-s 0-safe _ s > thres, where s1 is the current longitudinal position of the front vehicle, s0 is the current longitudinal position of the autonomous vehicle, safe _ s is a safe distance, and thres is a set threshold; the control module directly takes the cut-in threat evasion acceleration aq as the current required acceleration of the automatic driving vehicle without calculating the rear-end collision prevention acceleration a0 required by the automatic driving vehicle.
Further, when 0 is not less than s 1-s 0-safe _ s < thres and v0> v1, wherein v0 is the current speed of the automatic driving vehicle and v1 is the current speed of the front vehicle;
calculating an ideal acceleration ax required by the automatic driving vehicle, and taking the ideal acceleration ax as a rear-end collision prevention acceleration a 0; when the autonomous vehicle is operated at the ideal acceleration ax, the following conditions can be satisfied at time t:
s 1-s 0 ═ safe _ s, and v0t ═ v1t, where v0t is the vehicle speed at time t of the autonomous vehicle and v1t is the vehicle speed at time t of the preceding vehicle.
Further, when s 1-s 0-safe _ s <0, and v0> v1, an ideal acceleration ax required for the autonomous vehicle is calculated, and the ideal acceleration ax is taken as the rear-end collision prevention acceleration a 0.
Further, when s 1-s 0-safe _ s <0 and v0< ═ v1, the acceleration ay required by the autonomous vehicle is calculated, and the acceleration ay is taken as the rear-end collision prevention acceleration a 0; when the autonomous vehicle is operated with an acceleration ay, the condition can be satisfied at time t _ to _ safe: s 1-s 0 ═ safe _ s.
Further, the evasive cut-in threat acceleration aq required for automatically driving the vehicle is obtained by the following method,
calculating the acceleration az1 required by the autonomous vehicle, the autonomous vehicle being able to satisfy the condition at the moment tq when operating at an acceleration az 1: the speed of the automatic driving vehicle is the same as the speed of the front cut-in vehicle; the tq moment is the moment when the front cut-in vehicle cuts into the lane where the automatic driving vehicle is located;
calculating the acceleration az2 required by the autonomous vehicle, the autonomous vehicle being able to satisfy the condition at the moment tq when operating at an acceleration az 2: the distance between the automatic driving vehicle and the front cut-in vehicle is equal to the safe distance safe _ s;
the minimum of the acceleration az1 and the acceleration az2 is taken as the cut-in threat avoidance acceleration aq required for automatically driving the vehicle.
Further, when the prediction module predicts the vehicle running tracks of other lanes, a curve generation algorithm is adopted.
Further, the prediction module first determines a lateral intent of the vehicle based on the historical position, velocity, acceleration direction information of the vehicle and the current position, velocity, acceleration direction information of the vehicle before predicting the vehicle trajectory of the other lane.
2. A vehicle trajectory prediction apparatus based on history information, characterized by comprising:
the sensing module is used for acquiring the vehicle running information in front of the lane where the automatic driving vehicle is located and the vehicle running information of other lanes;
the prediction module is used for predicting the vehicle running tracks of other lanes and predicting the vehicle running information cut in ahead of the lane where the automatic driving vehicle is located;
and the control module is used for realizing the method.
3. A computer-readable storage medium having a computer program stored thereon, characterized in that: which when executed by a processor implements the method described above.
The invention has the following beneficial effects:
the invention discloses a method for predicting the running track of a vehicle in other lanes by a prediction module, and predicting the running information of a cut-in vehicle before the cut-in vehicle enters the lane where the automatic driving vehicle is located; the control module calculates the rear-end collision prevention acceleration a0 required by the automatic driving vehicle according to the running information of the vehicle in front of the lane where the automatic driving vehicle is located; and calculating a cut-in threat escape acceleration aq required by the automatic driving vehicle according to the predicted forward cut-in vehicle running information, and taking the minimum value of the rear-end collision preventing acceleration a0 and the cut-in threat escape acceleration aq as the current required acceleration of the automatic driving vehicle. The invention can lead the automatic driving vehicle to avoid the threat of the vehicle ahead of the current lane and the threat of the vehicle ahead cut into by other lanes, thereby realizing safer automatic driving than the general automatic driving (only avoiding the front vehicle).
Drawings
FIG. 1 is a general flow diagram of the process of the present invention;
FIG. 2 is a flow chart of the prediction module of the present invention predicting vehicle trajectories for other lanes;
FIG. 3 is a flow chart of the control module of the present invention calculating the current desired acceleration of the autonomous vehicle.
Detailed Description
The present invention is described in detail with reference to the embodiments shown in the drawings, but it should be understood that these embodiments are not intended to limit the present invention, and those skilled in the art should understand that functional, methodological, or structural equivalents or substitutions made by these embodiments are within the scope of the present invention.
The first embodiment is as follows:
acceleration control method for avoiding threat during automatic driving of vehicle
Sensing module for obtaining information
As shown in fig. 1, the sensing module obtains vehicle operation information in front of a lane in which the autonomous vehicle is located and vehicle operation information in other lanes. The vehicle information and the road information are obtained, and then the prediction module combines the vehicle information and the road information to find out which lane each vehicle belongs to, which is similar to a bird's-eye view of the road information.
(II) prediction module predicts forward cut vehicle operation information
As shown in fig. 1 and 2, the prediction module predicts the vehicle running track of other lanes and predicts the vehicle running information cut into the front of the lane where the autonomous vehicle is located, and the method is specifically implemented by the following method:
first, the lateral intent of the vehicle is determined, in other words whether the vehicle wants to continue driving on its own lane or to change lane into another lane in the future. The determination is based on the vehicle's historical position, speed, acceleration direction information (derived from the cached historical environmental information) and the vehicle's current position, speed, acceleration direction information. For example, if a vehicle is shifting to the left within 2 seconds before the current time that the vehicle is already very close to its lane edge and is heading to the left, then the probability of the vehicle making a lane change to the left in the future will be very high. The end result of the lateral intent would be an (intent, probabilistic) combination. For example, (left, 80%), (straight, 10%), (right, 10%).
After the future lateral intention of the vehicle is obtained, the prediction module predicts a future trajectory of the vehicle, and in the embodiment, the future trajectory prediction is a curve generation algorithm based on rules.
And (3) a curve generation algorithm:
for each curve, a mode of respectively processing in the transverse direction and the longitudinal direction is adopted. For the lateral direction, a5 th order polynomial of position with respect to time is used: the lateral displacement is a0+ a 1t + a2 (t ^2) + a3 (t ^3) + a4(t ^4) + a5 (t ^5), wherein t represents time. Thus there are a0 to a 56 unknowns. How to solve these 6 unknowns is described below.
If the lane change is required, the normal person drives, the normal person basically reaches the road center of the target road finally, and after the lane change is finished, the vehicle advances along the target road, the vehicle head is basically parallel to the target road, and basically no speed or acceleration exists in the transverse direction. We assume that the trajectory will eventually reach the road center of the target road that the intent is pointing to, and that the lateral velocity and acceleration are 0 at the end time. Since the center of the target road is reached last, the lateral displacement of the future trajectory end point with respect to the target road is 0. Thus, the lateral displacement, speed and acceleration of the future track end point relative to the target road are known. The lateral displacement, speed and acceleration of the vehicle at the current moment can be known through the sensed result, so that 6 equations can be provided, namely the above 6 unknowns can be solved (t0 represents the current moment, t1 represents the sampled lateral intention time):
the current transverse displacement is a0+ a 1t 0+ a2 (t0^2) + a3 (t0^3) + a4(t0^ 4) + a5 (t0^5)
The first derivative of the current transverse velocity is a1+2 a2 t0+3 a3 (t0^2) +4 a4(t0^3) +5 a5 (t0^4)
The second derivative of the current lateral acceleration (2 × a2+6 × a3 × t0+12 × a4 × t0^2) +20 × a5 ^ (t0^3)
The terminal transverse displacement is 0 ═ a0+ a1 ═ t1+ a2 ^ t1^2) + a3 ^ t1^3) + a4 ^ t1^4) + a5 (t1^5)
Terminal transverse velocity ═ first derivative of terminal transverse displacement ═ 0 ═ a1+2 ═ a2 ═ t1+3 ^ a3 ^ t1^2) +4 ^ a4(t1^3) +5 ^ a5 (t1^4)
The second derivative of the terminal transverse acceleration (0 ═ 2 ^ a2+6 ^ a3 ^ t1+12 ^ a4 ^ t1^2) +20 ^ a5 (t1^3)
For the longitudinal direction, it is not preferable to assume the longitudinal displacement of the end point of the future trajectory, and according to the driving habit of the normal person, it is preferable to assume that the longitudinal speed of the end point of the future trajectory is equal to the current speed, and the acceleration of the end point is 0 (for example, the lane change is made to the left, and after the lane change is completed, the normal person generally selects the uniform-speed driving). Thus there are only 5 equations (the equation with less endpoint displacement than in the lateral direction), so the longitudinal direction uses a4 th order polynomial of displacement versus time:
the longitudinal displacement is a0+ a 1t + a2 t ^2+ a3 t ^3+ a4 t ^ 4;
after obtaining the two polynomials in the transverse direction and the longitudinal direction, the transverse displacement and the longitudinal displacement of the vehicle, the transverse speed and the longitudinal speed (obtained by solving a first derivative of the polynomial), the transverse acceleration and the longitudinal acceleration (obtained by solving a second derivative of the polynomial) at any time from t0 to t1 can be obtained, and then a track starting from the time t0 and ending at the time t1 can be obtained.
For each vehicle, different intention completion times are sampled through a mathematical curve formula and the surrounding environment conditions, a plurality of possible tracks are fitted to each transverse intention, and then the most reasonable track is selected from the tracks to be used as the final track of each vehicle for each transverse intention. "reasonable trajectory" is defined as a trajectory closer to the historical driving style of the vehicle.
(III) the control module calculates the current required acceleration of the automatic driving vehicle
As shown in fig. 1 and 3, the control module calculates a rear-end collision prevention acceleration a0 required by the autonomous vehicle according to vehicle running information in front of a lane in which the autonomous vehicle is located; and calculating a cut-in threat escape acceleration aq required by the automatic driving vehicle according to the predicted forward cut-in vehicle running information, and taking the minimum value of the rear-end collision preventing acceleration a0 and the cut-in threat escape acceleration aq as the current required acceleration of the automatic driving vehicle.
The method for calculating the rear-end collision prevention acceleration a0 required by the automatic driving vehicle is realized by the following method:
when s 1-s 0-safe _ s > thres, in the formula, s1 is the current longitudinal position of the front vehicle, s0 is the current longitudinal position of the automatic driving vehicle, safe _ s is a safe distance, and thres is a set threshold; the control module directly takes the cut-in threat evasion acceleration aq as the current required acceleration of the automatic driving vehicle without calculating the rear-end collision prevention acceleration a0 required by the automatic driving vehicle.
When 0 is not less than s 1-s 0-safe _ s < thres and v0> v1, wherein v0 is the current speed of the automatic driving vehicle and v1 is the current speed of the front vehicle; calculating an ideal acceleration ax required by the automatic driving vehicle, and taking the ideal acceleration ax as a rear-end collision prevention acceleration a 0; when the autonomous vehicle is operated at the ideal acceleration ax, the following conditions can be satisfied at time t:
s 1-s 0 is safe _ s, and v0t is v1t, where v0t is the vehicle speed at time t of the autonomous vehicle, v1t is the vehicle speed at time t of the front vehicle, that is, the vehicle speed of the autonomous vehicle is the same as the vehicle speed of the front vehicle, and the distance between the autonomous vehicle and the front vehicle is a safe distance.
Ideal acceleration ax calculation method:
assume that the current time is 0 and assume that at a future time, time t, the autonomous vehicle is just a safe distance from the preceding vehicle and at a speed equal to the preceding vehicle. Then t and ax need to satisfy v0+ ax t-v 1+ a 1t, so that the automatic driving vehicle meets the condition that the speed of the automatic driving vehicle is equal to that of the preceding vehicle at the time t; t and ax also meet the requirement that the distance s11 (v 1t +0.5 a1 t) can ensure that the automatic driving vehicle keeps a safe distance from the preceding vehicle just from the current time to the preceding vehicle during the uniform acceleration running; the distance s01 from the current time to the time t, when the autonomous vehicle travels with the acceleration of ax and the uniform acceleration, is v0 × t +0.5 × ax × t; therefore, s 01-s 11 is the current distance between two vehicles, safe _ s, and the values of ax and t can be calculated by the above equation.
And when s 1-s 0-safe _ s is less than 0, and v0> v1, calculating the ideal acceleration ax required by the automatic driving vehicle, and taking the ideal acceleration ax as the rear-end collision prevention acceleration a 0. The ideal acceleration ax is calculated as above.
When s 1-s 0-safe _ s is less than 0 and v0< ═ v1, calculating the acceleration ay required by the automatic driving vehicle, and taking the acceleration ay as the rear-end collision prevention acceleration a 0; when the autonomous vehicle is operated with an acceleration ay, the condition can be satisfied at time t _ to _ safe: s 1-s 0 ═ safe _ s.
The evasive cut-in threat acceleration aq required for autonomous driving of the vehicle is obtained by:
calculating the acceleration az1 required by the autonomous vehicle, the autonomous vehicle being able to satisfy the condition at the moment tq when operating at an acceleration az 1: the speed of the automatic driving vehicle is the same as the speed of the front cut-in vehicle; the tq moment is the moment when the front cut-in vehicle cuts into the lane where the automatic driving vehicle is located;
calculating the acceleration az2 required by the autonomous vehicle, the autonomous vehicle being able to satisfy the condition at the moment tq when operating at an acceleration az 2: the distance between the automatic driving vehicle and the front cut-in vehicle is equal to the safe distance safe _ s;
the minimum of the acceleration az1 and the acceleration az2 is taken as the cut-in threat avoidance acceleration aq required for automatically driving the vehicle.
At time tq, if the distance between the front cut-in vehicle and the autonomous vehicle is greater than a set threshold thres, the cut-in threat avoidance acceleration aq does not need to be calculated.
Example two:
vehicle track prediction device based on historical information
The system comprises a sensing module, wherein the sensing module is used for acquiring the running information of the vehicle in front of a lane where the automatic driving vehicle is located and the running information of the vehicle in other lanes. The sensing module comprises a camera, a millimeter wave radar, a laser radar and other sensors, collects the surrounding environment state in real time, and further comprises a positioning module used for acquiring the position information of the vehicle.
And the prediction module is used for predicting the vehicle running tracks of other lanes and predicting the vehicle running information cut in ahead of the lane where the automatic driving vehicle is located.
And the control module is used for realizing the method in the first embodiment. Calculating the rear-end collision prevention acceleration a0 required by the automatic driving vehicle according to the running information of the vehicle in front of the lane in which the automatic driving vehicle is located; and calculating a cut-in threat escape acceleration aq required by the automatic driving vehicle according to the predicted forward cut-in vehicle running information, and taking the minimum value of the rear-end collision preventing acceleration a0 and the cut-in threat escape acceleration aq as the current required acceleration of the automatic driving vehicle.
Example three:
computer readable storage medium
The computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the method of one embodiment, calculating a current desired acceleration for the autonomous vehicle.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention, and they are not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention should be included in the scope of the present invention.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (10)
1. A control method for avoiding threat acceleration of an automatic driving vehicle is characterized by comprising the following steps:
the method comprises the steps that a sensing module obtains vehicle running information in front of a lane where an automatic driving vehicle is located and vehicle running information of other lanes;
the prediction module predicts the vehicle running tracks of other lanes and predicts the cut-in vehicle running information before the lane where the automatic driving vehicle is located;
the control module calculates the rear-end collision prevention acceleration a0 required by the automatic driving vehicle according to the running information of the vehicle in front of the lane where the automatic driving vehicle is located; and calculating a cut-in threat escape acceleration aq required by the automatic driving vehicle according to the predicted forward cut-in vehicle running information, and taking the minimum value of the rear-end collision preventing acceleration a0 and the cut-in threat escape acceleration aq as the current required acceleration of the automatic driving vehicle.
2. The autonomous vehicle threat avoidance acceleration control method of claim 1, characterized in that:
when s 1-s 0-safe _ s > thres, in the formula, s1 is the current longitudinal position of the front vehicle, s0 is the current longitudinal position of the automatic driving vehicle, safe _ s is a safe distance, and thres is a set threshold;
the control module directly takes the cut-in threat evasion acceleration aq as the current required acceleration of the automatic driving vehicle without calculating the rear-end collision prevention acceleration a0 required by the automatic driving vehicle.
3. The autonomous vehicle threat avoidance acceleration control method of claim 2, characterized in that:
when 0 is not less than s 1-s 0-safe _ s < thres and v0> v1, wherein v0 is the current speed of the automatic driving vehicle and v1 is the current speed of the front vehicle;
calculating an ideal acceleration ax required by the automatic driving vehicle, and taking the ideal acceleration ax as a rear-end collision prevention acceleration a 0; when the autonomous vehicle is operated at the ideal acceleration ax, the following conditions can be satisfied at time t:
s 1-s 0 ═ safe _ s, and v0t ═ v1t, where v0t is the vehicle speed at time t of the autonomous vehicle and v1t is the vehicle speed at time t of the preceding vehicle.
4. The autonomous vehicle threat avoidance acceleration control method of claim 3, characterized in that: and when s 1-s 0-safe _ s is less than 0, and v0> v1, calculating the ideal acceleration ax required by the automatic driving vehicle, and taking the ideal acceleration ax as the rear-end collision prevention acceleration a 0.
5. The autonomous vehicle threat avoidance acceleration control method of claim 3, characterized in that: when s 1-s 0-safe _ s is less than 0 and v0< ═ v1, calculating the acceleration ay required by the automatic driving vehicle, and taking the acceleration ay as the rear-end collision prevention acceleration a 0; when the autonomous vehicle is operated with an acceleration ay, the condition can be satisfied at time t _ to _ safe: s 1-s 0 ═ safe _ s.
6. The automated driving vehicle threat avoidance acceleration control method according to claim 1, wherein the avoidance cut-in threat acceleration aq required for the automated driving vehicle is obtained by,
calculating the acceleration az1 required by the autonomous vehicle, the autonomous vehicle being able to satisfy the condition at the moment tq when operating at an acceleration az 1: the speed of the automatic driving vehicle is the same as the speed of the front cut-in vehicle; the tq moment is the moment when the front cut-in vehicle cuts into the lane where the automatic driving vehicle is located;
calculating the acceleration az2 required by the autonomous vehicle, the autonomous vehicle being able to satisfy the condition at the moment tq when operating at an acceleration az 2: the distance between the automatic driving vehicle and the front cut-in vehicle is equal to the safe distance safe _ s;
the minimum of the acceleration az1 and the acceleration az2 is taken as the cut-in threat avoidance acceleration aq required for automatically driving the vehicle.
7. The autonomous vehicle threat-evading acceleration control method according to any one of claims 1 to 6, characterized in that: and when the prediction module predicts the vehicle running tracks of other lanes, a curve generation algorithm is adopted.
8. The autonomous vehicle threat avoidance acceleration control method of claim 7, characterized in that: the prediction module first determines a lateral intention of the vehicle based on a historical operating speed and an acceleration direction of the vehicle and a current speed and an acceleration direction of the vehicle before predicting the vehicle operating track of the other lane.
9. A vehicle trajectory prediction apparatus based on history information, characterized by comprising:
the sensing module is used for acquiring the vehicle running information in front of the lane where the automatic driving vehicle is located and the vehicle running information of other lanes;
the prediction module is used for predicting the vehicle running tracks of other lanes and predicting the vehicle running information cut in ahead of the lane where the automatic driving vehicle is located;
a control module for implementing the method of any one of claims 1 to 6.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: the computer program, when executed by a processor, implements the method of any of claims 1 to 6.
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