CN114394091B - A vehicle speed control method in the scene of traffic vehicles merging in an adaptive cruise system - Google Patents

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

A vehicle speed control method in an adaptive cruise control system under a traffic merging scenario

Technical Field

The invention relates to a vehicle speed control method, and in particular to a vehicle speed control method in a traffic merging scenario based on an adaptive cruise system.

Background Art

The Adaptive Cruise Control (ACC) system uses sensors installed on the car to detect the distance between the main vehicle and the vehicle in front. According to the relative distance between the two and the set speed, the ACC system sends instructions to the braking system and the engine control system to control the acceleration or deceleration of the vehicle to maintain a safe distance from the vehicle in front. The current adaptive cruise control system of the car mainly focuses on the distance control between the vehicle and the vehicle in front of the lane, that is, the following target, but pays little attention to the vehicles in the adjacent lanes. When the vehicle in the adjacent lane merges into the lane, the vehicle is set as the following target only when half of the traffic vehicle enters the lane. This will cause the vehicle to react lag. In order to increase the following distance to a safe distance in time, sudden braking will occur, and even accidents may occur. However, some existing control methods that consider the merging of traffic vehicles in advance do not consider specific collision forms such as side collisions and rear-end collisions when judging vehicle interference. There is a lack of pre-response to the traffic vehicles in the adjacent lane merging into the lane, and the prediction accuracy of the collision time needs to be improved; when controlling the speed of the vehicle, most of them blindly take conservative deceleration measures, which affects the traffic efficiency.

Some existing adaptive cruise control methods that focus on merging vehicles in adjacent lanes still have the following problems: they do not consider the specific trajectory of merging vehicles, nor the possible form of collision, and their accuracy needs to be improved; or when judging whether two vehicles interfere with each other, the geometric model of the vehicle is assumed to be a point, and the actual volume is not taken into account. In the collision judgment, the volume and shape of the vehicle itself are not sufficiently considered, and the possible form of interference between vehicles cannot be fully considered.

Summary of the invention

In order to solve the above technical problems existing in the existing adaptive cruise control system, the present invention provides a vehicle speed control method in a traffic merging scenario based on an adaptive cruise control system, comprising the following steps:

The first step is to collect the kinematic information of the vehicle and adjacent vehicles: including the speed, acceleration, yaw rate of the vehicle, the lateral distance, longitudinal distance, heading angle, yaw rate, longitudinal speed, lateral speed of adjacent vehicles relative to the vehicle, etc.

Step 2: Identify the merging intention of vehicles in adjacent lanes: Identify the left lane change, right lane change or lane keeping intention of vehicles in adjacent lanes, and mark vehicles with the intention of merging into the lane as merging vehicles;

Step 3: Predict the discrete trajectories of the merging vehicles and the vehicle:

Predict the merging discrete trajectory of the merging vehicle within the next ΔT time: The sampling frequency is f, and a merging discrete trajectory sequence of length ΔT×f is obtained, which contains the position, speed and heading angle information of the merging vehicle within the next ΔT time, and is converted to the ego-vehicle coordinate system at the current moment;

Predict the discrete trajectory of the ego vehicle in the future ΔT time: The sampling frequency is f, that is, the trajectory sequence of length ΔT×f is obtained, which contains the longitudinal position, lateral position, speed, and heading angle information of the ego vehicle in the future ΔT time relative to the current moment;

Step 4: Calculation of collision time:

Calculation of short-term collision time: The traversal method detects the overlap of the rectangular frames of the self-vehicle and the merging traffic vehicle in the predicted discrete trajectory sequence, and records the time corresponding to the first overlapped trajectory point as the collision time ttc;

If there is no overlap within the predicted trajectory during the rectangular frame overlap detection, a uniform velocity model is established to perform further long-term collision time calculation and collision situation identification;

Step 5: Calculate the expected acceleration of the vehicle based on the collision time ttc and collision situation calculated in step 4;

Step 6: The vehicle adaptive cruise system communicates with the braking system and the driving system to generate appropriate braking pressure or engine output power, and controls the vehicle to travel at the desired acceleration until the adaptive cruise system's following target switches to a merging vehicle or the longitudinal distance to the vehicle in front of the current lane is less than or equal to the following distance th _{v h} .

Furthermore, the rectangular frame overlap detection described in the fourth step includes the following steps:

Step 1: Calculate the coordinates (x _corner ,y _corner ) _{fl, fr, rl, rr} of the four corners of the rectangular frame of the vehicle relative to the trajectory of the merging vehicle at the same time through coordinate system conversion;

且

表示该角点与交通车发生碰撞；Step 2: Compare the corner coordinates (x _corner ,y _corner ) _fl,fr,rl,rr of the ego vehicle with the length l _t and width w _t of the rectangular box of the merging vehicle to determine whether the rectangular box of the ego vehicle has a corner that interferes with the merging vehicle. If a corner satisfies

and

Indicates that the corner point collides with the traffic vehicle;

Step 3: Calculate the coordinates (x' _corner ,y' _corner ) _{fl, fr, rl, rr} of the four corner points of the rectangular box of the merging vehicle relative to the trajectory point of the vehicle at the same time through coordinate system conversion;

且

表示该角点与自车发生碰撞；Step 4: Compare the corner coordinates (x' _corner ,y' _corner ) _fl,fr,rl,rr of the merging vehicle with the length l _h and width w _h of the ego vehicle's rectangular frame to determine whether there is a corner point of the merging vehicle's rectangular frame that interferes with the ego vehicle. If a corner point satisfies

and

Indicates that the corner point collides with the vehicle;

Step 5, referring to Step 1 to Step 4, the overlap of the rectangular boxes of the predicted trajectory sequence is detected by the traversal method, the predicted trajectory sequence that first detects the overlap of the rectangular boxes is indexed as k _collision , and the collision time is recorded as ttc=k _collision /f, ttc≤ΔT.

Furthermore, the long-term collision time calculation and collision situation determination described in the fourth step include the following steps:

Step 1: extract the position, speed and heading angle information of the vehicle and the merging vehicle at the last moment of trajectory prediction k = ΔT × f;

为k＝ΔT×f时刻并道交通车相对同一时刻自车的航向角，v_xk为k＝ΔT×f时刻并道交通车与自车的纵向相对速度，ε表示车辆直线行驶时航向角的正常波动范围，若

碰撞情形及碰撞时间计算如下：Step 2: Assume that the two vehicles will continue to move in a straight line at a constant speed from now on.

is the heading angle of the merging vehicle relative to the own vehicle at the same time at k = ΔT × f, v _xk is the longitudinal relative speed of the merging vehicle and the own vehicle at k = ΔT × f, ε represents the normal fluctuation range of the heading angle when the vehicle is traveling in a straight line, if

The collision scenarios and collision time are calculated as follows:

Collision Scenario 0:

v_xk＜0，执行步骤3、4、5；like

v _xk ＜0, execute steps 3, 4, and 5;

v_xk＜0时，计算纵向碰撞时间ttc_x和侧向碰撞时间ttc_y；纵侧向碰撞时间计算方法如下式所示：Step 3

When v _xk <0, calculate the longitudinal collision time ttc _x and the lateral collision time ttc _y ; the longitudinal and lateral collision time calculation method is shown in the following formula:

In the above formula, _xk , _yk , _vxk , and _vyk are the longitudinal relative distance, lateral relative distance, longitudinal relative speed, and lateral relative speed of the merging vehicle and the vehicle at time k = ΔT × f.

Step 4: Compare the longitudinal and lateral collision times of the same group to determine the collision situation, as follows:

If ttc _x,1 ≥ttc _y,1 , it is collision situation I, which means that the front of the vehicle collides with the rear corner of the merging vehicle;

If ttc _x,2 ≥ttc _y,2 &ttc _x,1 ＜ttc _y,1 , it is collision situation II, which means that the front corner of the vehicle collides with the side of the merging vehicle at an angle.

If ttc _x,3 ≥ttc _y,3 &ttc _x,2 ＜ttc _y,2 , it is collision situation III, which means that the front corner of the merging vehicle collides with the side of the vehicle at an angle.

If ttc _x,4 ≥ttc _y,4 &ttc _x,3 ＜ttc _y,3 , it is collision situation IV, which means that the head of the merging vehicle collides with the corner of the rear of the own vehicle side by side;

Step 5: Calculate the corresponding collision time ttc according to the determined collision situation. The calculation formula is as follows:

Collision Scenario I:

Collision Scenario II:

Collision Scenario III:

Collision Scenario IV:

Furthermore, the method for calculating the expected acceleration of the vehicle in the fifth step is as follows:

Step 1: If ttc≤ΔT or the determined collision situation is 0, I or II, the expected braking deceleration of the vehicle is:

Step 2: If the collision situation is III or IV, there is no vehicle ahead in the current lane, or the longitudinal distance to the vehicle ahead in the current lane is x _follow ≥ 1.2 _th v _h , then the expected acceleration of the ego vehicle is:

Step 3: If the determined collision situation is III or IV, there is a leading vehicle in the current lane, and the longitudinal distance x _follow to the leading vehicle in the current lane is <1.2 _th v _h , then the expected braking deceleration of the ego vehicle is the same as step 1;

Wherein, a _bmax and a _amax in steps 1 to 3 are the maximum braking acceleration and maximum acceleration that the ego vehicle can achieve, respectively, v _h is the ego vehicle speed at the current moment, and t _h is the following distance set by the vehicle adaptive cruise control system.

Beneficial effects of the present invention:

Compared with the prior art, the present invention fully considers the merging intention of traffic vehicles and the possible specific driving trajectories of the own vehicle and the merging traffic vehicles in the future, and greatly improves the prediction accuracy of collisions in a short time by considering the actual size of the vehicles through rectangular frame overlap detection; further, by considering the actual size of the vehicles for long-term collision time calculation and collision situation judgment, the prediction ability of traffic conditions in a long time is enhanced; most of the prior arts will perform different degrees of braking actions when facing the merging conditions of traffic vehicles, while the present invention calculates the expected acceleration of the own vehicle according to the collision time and collision situation, controls the vehicle to brake to increase the distance between the following vehicles in advance and avoid collision risks, or accelerates to avoid collision risks and improve traffic efficiency.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is an overall flow chart of the present invention.

FIG. 2 is a schematic diagram of the present invention for working conditions.

FIG3 is a schematic diagram of the calculation of the short-time collision time and rectangular frame overlap detection according to the present invention.

FIG. 4 is a schematic diagram of the calculation flow of the short-time collision time and rectangular frame overlap detection according to the present invention.

FIG. 5 is a schematic diagram of four collision situations in the long-term collision time calculation and collision situation identification of the present invention.

FIG6 is a schematic diagram of the long-term collision time calculation and collision situation determination process of the present invention.

FIG. 7 is a schematic diagram of a flow chart of the calculation of the desired acceleration of the vehicle according to the present invention.

The annotations in the figure are as follows:

1. The vehicle itself, 2. The merging vehicle, 3. The vehicle in front of the current lane, 4. The four corner points of the rectangular box of the vehicle itself, 5. The four corner points of the rectangular box of the merging vehicle.

DETAILED DESCRIPTION

Please refer to Figure 1-7:

The present invention provides a vehicle speed control method in a traffic merging scenario based on an adaptive cruise system, comprising the following steps:

S10, collecting kinematic information of the vehicle 1 and adjacent vehicles: including the speed, acceleration, and yaw rate of the vehicle 1, and the lateral distance, longitudinal distance, heading angle, yaw rate, longitudinal velocity, and lateral velocity of adjacent vehicles relative to the vehicle.

S20. Identify the merging intention of vehicles in adjacent lanes: The method is: use the vehicle left lane change, right lane change and lane keeping data in the public natural driving data set to train a hidden Markov model to identify the left lane change, right lane change or lane keeping intention of vehicles in adjacent lanes; mark the vehicle with the intention to merge into the current lane as merging vehicle 2.

S30, predicting the discrete trajectory of the merging vehicle 2 within the future ΔT time: the trajectory point is the position of the geometric center of the vehicle at the corresponding moment, the sampling frequency is f, and the trajectory sequence of length ΔT×f is obtained, which includes the position, speed and heading angle information of the merging vehicle 2 within the future ΔT time, and is converted to the current moment's self-vehicle coordinate system. The trajectory prediction method is: using the vehicle lane change data in the public natural driving data set, extracting the trajectory fragments when the vehicle changes lanes to the left and right, using a neural network to train the vehicle lane change trajectory prediction models for the left and right lane changes, respectively, with a prediction time of ΔT, and obtaining the discrete trajectory sequence of the merging vehicle 2.

S40, predicting the discrete trajectory of vehicle 1 in the future ΔT time: the trajectory point is the position of the geometric center of the vehicle at the corresponding moment, the sampling frequency is f, that is, a trajectory sequence of length ΔT×f is obtained, which includes the longitudinal position, lateral position, vehicle speed, and heading angle information of vehicle 1 in the future ΔT time relative to the current moment. The method is: according to the longitudinal speed and yaw rate of vehicle 1 at the current moment, the future trajectory of vehicle 1 is predicted using a constant turn rate and speed model, and the state transfer equation is:

表示k时刻自车相对当前时刻的航向角，

表示k时刻自车的角速度；Δt为采样步长。In the formula, the state quantity _xk represents the longitudinal position of the vehicle at time k relative to the current time, _yk represents the lateral position of the vehicle at time k relative to the current time, and _vk represents the speed of the vehicle at time k.

represents the heading angle of the vehicle at time k relative to the current time,

represents the angular velocity of the vehicle at time k; Δt is the sampling step.

S50, short-term collision time calculation: The traversal method performs a rectangular frame overlap detection on the predicted discrete trajectory sequence between the vehicle 1 and the merging vehicle 2, and records the time corresponding to the first overlapped trajectory point as the collision time ttc. The rectangular frame overlap detection, as shown in Figures 1, 3 and 4, includes the following steps:

S51, by coordinate system conversion, respectively calculate the coordinates (x _corner ,y _corner ) _{fl, fr, rl, rr} of the four corner points of the rectangular frame of vehicle 1 relative to the trajectory point of the merging vehicle 2 at the same time;

且

表示该角点与交通车发生碰撞；S52, compare the corner coordinates (x _corner ,y _corner ) _fl,fr,rl,rr of the ego vehicle with the length l _t and width w _t of the rectangular box of the merging vehicle, and determine whether the rectangular box of ego vehicle 1 has a corner that interferes with the merging vehicle 2. If a corner satisfies

and

Indicates that the corner point collides with the traffic vehicle;

S53, by coordinate system conversion, respectively calculating the coordinates (x' _corner ,y' _corner ) _{fl, fr, rl, rr} of the four corner points of the rectangular frame of the merging vehicle 2 relative to the trajectory point of the vehicle 1 at the same time;

且

表示该角点与自车发生碰撞；S54, compare the corner coordinates (x' _corner ,y' _corner ) _fl,fr,rl,rr of the merging vehicle 2 with the length l _h and width w _h of the rectangular frame of the merging vehicle 1 to determine whether the rectangular frame of the merging vehicle 2 has a corner that interferes with the merging vehicle 1. If a corner satisfies

and

Indicates that the corner point collides with the vehicle;

S55 , referring to S51 to S54 , using the traversal method to detect the overlap of the rectangular boxes of the predicted trajectory sequence, the predicted trajectory sequence that first detects the overlap of the rectangular boxes is indexed as k _collision , and the collision time is recorded as ttc=k _collision /f, ttc≤ΔT.

S60, long-term collision time calculation and collision situation determination: If there is no overlap within the predicted trajectory range in the rectangular frame overlap detection in S50, a uniform speed model is established to perform further collision time prediction, as shown in FIG. 1 , FIG. 5 and FIG. 6 , including the following steps:

S61, extracting the position, speed and heading angle information of the vehicle 1 and the merging vehicle 2 at the last moment of trajectory prediction k=ΔT×f;

为k＝ΔT×f时刻并道交通车2相对同一时刻自车1的航向角，v_xk为k＝ΔT×f时刻并道交通车2与自车1的纵向相对速度，ε表示车辆直线行驶时航向角的正常波动范围，为一较小正实数，若

v_xk＜0，碰撞情形及碰撞时间计算如下：S62. Assume that the two vehicles continue to travel in a straight line at a constant speed.

is the heading angle of the merging vehicle 2 relative to the own vehicle 1 at the same time at k = ΔT × f, v _xk is the longitudinal relative speed of the merging vehicle 2 and the own vehicle 1 at the time k = ΔT × f, ε represents the normal fluctuation range of the heading angle when the vehicle is traveling in a straight line, which is a small positive real number.

v _xk ＜0, the collision situation and collision time are calculated as follows:

Collision Scenario 0:

v_xk＜0，执行S63、S64、S65；like

v _xk ＜0, execute S63, S64, S65;

v_xk＜0时，计算纵向碰撞时间ttc_x和侧向碰撞时间ttc_y；纵侧向碰撞时间计算方法如下式所示：S63,

When v _xk <0, calculate the longitudinal collision time ttc _x and the lateral collision time ttc _y ; the longitudinal and lateral collision time calculation method is shown in the following formula:

In the above formula, _xk , _yk , _vxk , and _vyk are the longitudinal relative distance, lateral relative distance, longitudinal relative speed, and lateral relative speed of the merging vehicle 2 and the vehicle 1 at time k = ΔT × f.

S64. Compare the longitudinal and lateral collision times of the same group to determine the collision situation in the following manner:

If ttc _x,1 ≥ttc _y,1 , it is collision situation I, which means that the head of vehicle 1 collides with the rear corner of merging vehicle 2;

If ttc _x,2 ≥ttc _y,2 &ttc _x,1 ＜ttc _y,1 , it is collision situation II, which means that the front corner of vehicle 1 collides with the side of merging vehicle 2 at an angle.

If ttc _x,3 ≥ttc _y,3 &ttc _x,2 ＜ttc _y,2 , it is collision situation III, which means that the front corner of the merging vehicle 2 collides with the side of the vehicle 1 at an angle.

If ttc _x,4 ≥ttc _y,4 &ttc _x,3 ＜ttc _y,3 , it is collision situation IV, which means that the head of the merging vehicle 2 collides with the rear corner of the vehicle 1 side by side;

S65. Calculate the corresponding collision time ttc according to the collision situation determined in S64. The calculation formula is as follows:

Collision Scenario I:

Collision Scenario II:

Collision Scenario III:

Collision Scenario IV:

S70, calculating the expected acceleration of vehicle 1 according to the collision time ttc calculated in S50 and S60, the method is as follows:

S71. If ttc≤ΔT or the collision situation determined in S60 is 0, I or II, the expected braking deceleration of vehicle 1 is:

S72. If the collision situation determined in S60 is III or IV, there is no preceding vehicle in the current lane, or the longitudinal distance x _follow from the preceding vehicle 3 in the current lane is ≥1.2 _th v _h , the expected acceleration of the ego vehicle is:

S73, if the collision situation determined in S60 is III or IV, there is a preceding vehicle in the current lane, and the longitudinal distance x _follow from the preceding vehicle 3 in the current lane is less than 1.2 _th v _h , the expected braking deceleration of the ego vehicle is the same as that in S71;

Wherein, a _bmax and a _amax in S71-S73 are respectively the maximum braking acceleration and maximum acceleration that the vehicle 1 can reach, v _h is the speed of the vehicle 1 at the current moment, and t _h is the following distance set by the vehicle adaptive cruise control system.

S80: The vehicle adaptive cruise control system communicates with the braking system and the driving system to generate appropriate braking pressure or engine output power, and controls the vehicle to travel at a desired acceleration until the adaptive cruise control system's following target switches to the merging vehicle 2, or the longitudinal distance to the preceding vehicle 3 in the current lane is less than or equal to the following distance th _{v h} .

Claims (2)

1. A vehicle speed control method in a traffic merging scenario in an adaptive cruise control system, characterized in that it comprises the following steps: The first step is to collect the kinematic information of the vehicle and adjacent vehicles: including the speed, acceleration, yaw rate of the vehicle, the lateral distance, longitudinal distance, heading angle, yaw rate, longitudinal speed, lateral speed of adjacent vehicles relative to the vehicle, etc. Step 2: Identify the merging intention of vehicles in adjacent lanes: Identify the left lane change, right lane change or lane keeping intention of vehicles in adjacent lanes, and mark vehicles with the intention of merging into the lane as merging vehicles; Step 3: Predict the discrete trajectories of the merging vehicles and the vehicle: Predict the merging discrete trajectory of the merging vehicle within the next ΔT time: The sampling frequency is f, and a merging discrete trajectory sequence of length ΔT×f is obtained, which contains the position, speed and heading angle information of the merging vehicle within the next ΔT time, and is converted to the ego-vehicle coordinate system at the current moment; Predict the discrete trajectory of the ego vehicle in the future ΔT time: the sampling frequency is f, that is, the trajectory sequence of length ΔT×f is obtained, which contains the longitudinal position, lateral position, speed, and heading angle information of the ego vehicle in the future ΔT time relative to the current moment; Step 4: Calculation of collision time: Calculation of short-term collision time: The traversal method detects the overlap of the rectangular frames of the self-vehicle and the merging traffic vehicle in the predicted discrete trajectory sequence, and records the time corresponding to the first overlapped trajectory point as the collision time ttc; If there is no overlap within the predicted trajectory range during the rectangular frame overlap detection, a uniform velocity model is established to perform further long-term collision time calculation and collision situation identification, including the following steps: Step 1: extract the position, speed and heading angle information of the vehicle and the merging vehicle at the last moment of trajectory prediction k = ΔT × f; Step 2: Assume that the two vehicles will continue to move in a straight line at a constant speed from now on.

is the heading angle of the merging vehicle relative to the own vehicle at the same time at k = ΔT × f, v _xk is the longitudinal relative speed of the merging vehicle and the own vehicle at k = ΔT × f, ε represents the normal fluctuation range of the heading angle when the vehicle is traveling in a straight line, if

v _xk ＜0, the collision situation and collision time are calculated as follows: Collision Scenario 0:

like

v _xk ＜0, execute steps 3, 4, and 5; Step 3

When v _xk <0, calculate the longitudinal collision time ttc _x and the lateral collision time ttc _y ; the longitudinal and lateral collision time calculation method is shown in the following formula:

In the above formula, _xk , _yk , _vxk , and _vyk are the longitudinal relative distance, lateral relative distance, longitudinal relative speed, and lateral relative speed of the merging vehicle and the vehicle at time k = ΔT × f.

Step 4: Compare the longitudinal and lateral collision times of the same group to determine the collision situation, as follows: If ttc _x,1 ≥ttc _y,1 , it is collision situation I, which means that the front of the vehicle collides with the rear corner of the merging vehicle; If ttc _x,2 ≥ttc _y,2 &ttc _x,1 ＜ttc _y,1 , it is collision situation II, which means that the front corner of the vehicle collides with the side of the merging vehicle at an angle. If ttc _x,3 ≥ttc _y,3 &ttc _x,2 ＜ttc _y,2 , it is collision situation III, which means that the front corner of the merging vehicle collides with the side of the vehicle at an angle. If ttc _x,4 ≥ttc _y,4 &ttc _x,3 ＜ttc _y,3 , it is collision situation IV, which means that the head of the merging vehicle collides with the corner of the rear of the own vehicle side by side; Step 5: Calculate the corresponding collision time ttc according to the determined collision situation. The calculation formula is as follows: Collision Scenario I:

Collision Scenario II:

Collision Scenario III:

Collision Scenario IV:

Step 5: Calculate the expected acceleration of the vehicle based on the collision time ttc and collision situation calculated in step 4. The method is as follows: Step 1: If ttc≤ΔT or the determined collision situation is 0, I or II, the expected braking deceleration of the vehicle is:

Step 2: If the collision situation is III or IV, there is no vehicle ahead in the current lane, or the longitudinal distance to the vehicle ahead in the current lane is x _follow ≥ 1.2 _th v _h , then the expected acceleration of the ego vehicle is:

Step 3: If the determined collision situation is III or IV, there is a leading vehicle in the current lane, and the longitudinal distance x _follow to the leading vehicle in the current lane is <1.2 _th v _h , then the expected braking deceleration of the ego vehicle is the same as step 1; Wherein, a _bmax and a _amax in steps 1 to 3 are respectively the maximum braking acceleration and maximum acceleration that the ego vehicle can achieve, v _h is the ego vehicle speed at the current moment, and t _h is the following distance set by the vehicle adaptive cruise control system; Step 6: The vehicle adaptive cruise system communicates with the braking system and the driving system to generate appropriate braking pressure or engine output power, and controls the vehicle to travel at the desired acceleration until the adaptive cruise system's following target switches to a merging vehicle or the longitudinal distance to the vehicle in front of the current lane is less than or equal to the following distance th _{v h} . 2. The vehicle speed control method in a traffic merging scenario in an adaptive cruise control system according to claim 1, characterized in that: the rectangular frame overlap detection in the fourth step comprises the following steps: Step 1: Calculate the coordinates (x _corner ,y _corner ) _{fl, fr, rl, rr} of the four corners of the rectangular frame of the vehicle relative to the trajectory of the merging vehicle at the same time through coordinate system conversion; Step 2: Compare the corner coordinates (x _corner ,y _corner ) _fl,fr,rl,rr of the ego vehicle with the length l _t and width w _t of the rectangular box of the merging vehicle to determine whether the rectangular box of the ego vehicle has a corner that interferes with the merging vehicle. If a corner satisfies

and

Indicates that the corner point collides with the traffic vehicle; Step 3: Calculate the coordinates (x' _corner ,y' _corner ) _{fl, fr, rl, rr} of the four corner points of the rectangular box of the merging vehicle relative to the trajectory point of the vehicle at the same time through coordinate system conversion; Step 4: Compare the corner coordinates (x' _corner ,y' _corner ) _fl,fr,rl,rr of the merging vehicle with the length l _h and width w _h of the ego vehicle's rectangular frame to determine whether there is a corner point of the merging vehicle's rectangular frame that interferes with the ego vehicle. If a corner point satisfies

and

Indicates that the corner point collides with the vehicle; Step 5, referring to Step 1 to Step 4, the overlap of the rectangular boxes of the predicted trajectory sequence is detected by the traversal method, the predicted trajectory sequence that first detects the overlap of the rectangular boxes is indexed as k _collision , and the collision time is recorded as ttc=k _collision /f, ttc≤ΔT.

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