CN114926987A - Signalized intersection right-turning vehicle lane-borrowing overtaking driving guiding method and system - Google Patents

Abstract

The invention relates to a method and a system for guiding a vehicle turning right at a signalized intersection to overtake a vehicle. The system includes a roadside unit for collecting road traffic information in real time, a main control device and a vehicle-mounted unit connected to the roadside unit. The roadside unit communicates with the vehicle-mounted unit, and sends the data information collected by the vehicle equipped with the vehicle-mounted unit to the main control device in real time, and at the same time sends the control instruction information of the main control device to the vehicle; the main control device includes a data storage module, Data processing module, time recording module, time calculation module, dissipation time calculation module, signal light judgment module, traffic state detection module, lane change trajectory planning module, control signal transmission module; using this system, the social vehicles that turn right can be guided to drive to In the "increased" lanes, delays caused by bus obstructions are reduced, the efficiency of crossing traffic is improved, and the use efficiency of road space is improved.

Description

A method and system for guiding a vehicle turning right at a signalized intersection to overtake a vehicle

technical field

The invention belongs not only to the field of intelligent transportation, but also to the field of information communication, and in particular to a method and a system for guiding a vehicle turning right at a signal intersection to overtake a vehicle.

Background technique

In order to promote bus priority, it is a feasible way for buses to use the right-turn lane to give priority to traffic, which has been widely used in my country. However, the bus priority method can easily hinder the passage of right-turn vehicles and increase the delay of right-turn vehicles. In addition, when the number of entrance and exit lanes does not match, the bus is prone to traffic accidents when the bus is near the exit road and social vehicles are rushing to the lane. Increase bus delays.

The width of the road lane is an important content in road design. According to the "Technical Standards for Highway Engineering", the width of the road lane is 3.0m to 3.75m. At present, there are a large number of roads of 9m or more than 9m and less than 15m in our country. The width of the roadway of these roads can run three vehicles in parallel, but they are often divided into two lanes, which wastes road space data.

With the development of autonomous driving technology, the lateral swing of autonomous vehicles is greatly reduced, and it is possible to adjust and compress the lateral spacing of vehicles under the development trend of autonomous driving, especially when right-turning vehicles at signalized intersections are blocked by vehicles ahead , How to use the limited space of the intersection to guide the right-turning vehicles to overtake through the multi-vehicle coordination technology and intelligent vehicle control technology, improve the traffic efficiency of the intersection and improve the use efficiency of road space is an urgent problem to be solved.

SUMMARY OF THE INVENTION

The present invention provides a method for guiding right-turning vehicles to overtake in the environment of autonomous vehicle driving signal intersections. The method can reduce obstacles caused by buses by guiding right-turning social vehicles to drive into the "increased" lanes. delays, improve the efficiency of crossing traffic, and at the same time improve the efficiency of the use of road space.

To achieve the above object, the present invention adopts the following technical solutions:

A method for guiding a vehicle turning right at a signalized intersection to overtake a vehicle, which specifically includes the following steps:

Step S1, set the detection range within a certain distance from the stop line, the roadside unit detects the arrival of the right-turn vehicle A followed by the bus in the right lane, and record the time when the right-turn vehicle A arrives within the detection range as T1;

Step S2, determine whether the status of the signal light at time T1 is green; if so, go to step S3; if not, go to step S15;

Step S3, judging the time point of the status of the green light signal; if it is in the middle and late stages of the green light, and the queued vehicles in front of the right-turning vehicle A have dissipated, then go to step S4; if it is the early green light, there is still unreleased before the stop line queuing vehicles, then go to step S8;

Step S4, according to the current distance LA and the current speed V of the right-turn vehicle A from the stop line, predict the time length Ty required to reach the stop line, Ty=LA/V, then the time when the right-turn vehicle A arrives at the stop line is T1+Ty ;

Step S5: Set the initial time of turning on the green light of the traffic direction phase to be T0, the length of the green light cycle to be L1, the length of the red light cycle to be R1, and to calculate the end time of the green light phase according to the length of the green light cycle as T0+L1, and determine T0+L1>T1+Ty ? If yes, it indicates that the right-turning vehicle A can pass normally within the green light phase, then go to step S6; if no, it indicates that the right-turning vehicle A cannot reach the stop line within the green light phase, then go to step S7;

Step S6, the roadside unit sends the guidance information to the vehicle-mounted unit of the right-turning vehicle A to guide the right-turning vehicle A to accelerate through;

Step S7: The traffic state detection module detects the vehicles in front of the right-turning vehicle A, and determines the obstructing vehicles Z1, Z2... in front of the same lane of the right-turning vehicle A and the obstructing vehicles C1, C2... in front of the adjacent lanes of the right-turning vehicle A ; When determining an obstructing vehicle, according to the distance of each vehicle in front of the right-turning vehicle A from the stop line and its current speed, calculate the length of each vehicle passing through the stop line, and determine the length of each vehicle passing the stop line according to the length of each vehicle passing the stop line. The time when the green light phase ends T0+L1 > the time when the vehicle in front of the right-turning vehicle A passes the stop line? If it is, it means that the vehicle in front of the right-turning vehicle A can pass normally; if not, it means that the vehicle in front of the right-turning vehicle A cannot pass, which is an obstacle to the vehicle;

Step S8, calculate the time length Td for the queuing vehicle to dissipate, and the calculation formula of the queuing vehicle dissipation time length is as follows:

T _d =q*re /( _n *Sq)

In the formula: T _d is the queuing vehicle dissipation time, s; q is the vehicle arrival rate of the passing phase, pcu/h; r _e is the effective red light time of the passing phase, s; n is the number of lanes corresponding to the passing phase; S is the single vehicle Channel saturation flow rate, pcu/h;

Step S9, judge T0+L1>T0+Td+Ty? If yes, it indicates that the right-turning vehicle A can still reach the stop line after the queued vehicles in the previous signal cycle are dissipated, then go to step S6; if not, it indicates that the queued vehicles in the previous cycle cannot completely dissipate, then go to step S7;

Step S10: In order to ensure that the right-turning vehicle A overtaking does not affect the normal driving vehicles in this direction, the right-turning overtaking vehicle A should be completed before the end of the red light period of this phase, and read the time Tg=T0+ when the red light of this phase ends. L1+R1;

Step S11, according to the current distance between the right-turning vehicle A and the stop line, predict the duration Tw of the right-turning vehicle A traveling to the stop line according to the expected overtaking trajectory line;

Tw=Th+Tf

Tf=Lb/V

In the formula, Th is the time required for the right-turning vehicle A to change lanes, and its value ranges from 3s to 8s, Tf is the time to travel to the stop line after changing lanes, and Lb is the virtual time after the right-turning vehicle A changes lanes to increase. The distance from the back of the lane to the stop line, V is the speed of the right-turn vehicle A;

Step S12, determine whether T1+Tw>Tg? If no, it indicates that the vehicle can complete the right turn before the end of the red light period of this phase, then go to step S13; if yes, it indicates that it is not feasible, then go to step S15;

Step S13: The main control device sends guidance information to the obstructing vehicles Z1, Z2... in front of the same lane of the right-turning vehicle A and the vehicles C1, C2... in front of the adjacent lane of the right-turning vehicle A, so as to guide the obstructing vehicles to approach the lane edge line to decelerate drive;

Step S14, the main control device guides the right-turning vehicle A to overtake and drive right-turning;

In step S15, the roadside unit sends guidance information to the vehicle-mounted unit of the vehicle A turning right to guide the vehicle A to decelerate.

As a preference of the present invention, the planning method of the expected overtaking trajectory line of the right-turning vehicle A in step S11 is as follows;

In the formula, x _t and y _t are the abscissa and ordinate values of the right-turning vehicle A at time t, V _t is the speed of the x-axis direction at time t, w is the lane width, and t _f is the planning time required for the vehicle to change lanes, usually t _f > 3s.

As a preferred option of the present invention, when the vehicle A turns right in step S14 and changes lanes, the risk assessment module in the main control device needs to determine the potential field distribution of the overtaking vehicles changing lanes according to the road potential field model, so as to evaluate the risk of the vehicle changing lanes , obtain a feasible set of vehicle lane-changing trajectories within the scope of the safety domain; if the potential field safety critical value is C, then the planned expected overtaking trajectory line when the right-turning vehicle A passes by the lane needs to satisfy both E _S1 < C and E _S2 <C condition, it can be regarded as driving within the safe range; wherein, the road potential field model expression is as follows:

表示右转车辆A指向边界线j1的距离矢量；同理,

表示右转车辆A指向边界线j2的距离矢量，ρ为道路边界场系数。In the formula, E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoys of adjacent lanes when the right-turning vehicle A changes lanes to overtake, and the y-axis coordinate of the right-turning vehicle A at time t is y _t , A The boundary j1 and j2 axes of the adjacent lanes of the vehicle are y _{s, j1} , y _{s, j2} ,

Represents the distance vector of the right-turning vehicle A pointing to the boundary line j1; in the same way,

It represents the distance vector of the right-turning vehicle A pointing to the boundary line j2, and ρ is the road boundary field coefficient.

As a preference of the present invention, in step S14, the main control device guides the right-turning vehicle A to overtake a right-turn and drive as follows: the main control device first passes the lane-changing trajectory of the vehicle planned by the lane-changing trajectory planning module within the scope of the safety zone through the lane-changing trajectory. The control signal sending module sends the control signal to the roadside unit in real time, and the roadside unit transmits it to the vehicle-mounted unit through LTE-V/5G communication. After receiving the signal, the vehicle-mounted unit feeds back to the vehicle control module of the right-turning vehicle A, and the vehicle control module plans the trajectory line. For reference, the trajectory coordinates and vehicle speed of the right-turning vehicle A changing lanes are solved through online optimization.

As a further preference of the present invention, the vehicle control module solves the trajectory coordinates and vehicle speed of the right-turning vehicle A changing lanes as follows:

A nonlinear dynamic prediction model of vehicle motion is established, where L is the wheelbase of the own vehicle, and L _f is the distance from the center of mass to the foremost segment of the own vehicle; the state variables and control input of the own vehicle of the vehicle turning right and overtaking are X _t = [x _t , y _t , θ _t , v _t ] ^T and μ _t = [δ _t , at _t ] ^T , (x _t , y _t ) are the position coordinates of the vehicle at time t, and θ _t is the transverse direction of the vehicle at time t Swing angle, v _t is the speed of the vehicle at time t, δ _t is the steering angle of the front wheel at time t of the vehicle, and a _t is the acceleration of the vehicle at time t;

Divide the Th time step into N _p steps, and use the following formula to derive the kinematic state of the vehicle at step k+1 from the state at step k:

表示在总的时间步为p时，车辆t时刻第k+1步的横坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的纵坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的横摆角，

表示在总的时间步为p时，车辆t时刻第k+1步的速度；

定义同上，是第k步的量，

表示在总的时间步为p时，车辆t时刻第k步的加速度；Th为右转车辆A在初始车道准备换道开始至右转车辆A换道完成用消耗时间。where:

represents the abscissa of the k+1th step at time t of the vehicle when the total time step is p,

represents the ordinate of the k+1th step at time t of the vehicle when the total time step is p,

represents the yaw angle of the k+1th step at time t of the vehicle when the total time step is p,

Indicates the speed of the k+1th step of the vehicle at time t when the total time step is p;

The definition is the same as above, it is the amount of the kth step,

When the total time step is p, the acceleration of the vehicle at the k-th step at time t; Th is the elapsed time from the start of the right-turn vehicle A preparing to change lanes in the initial lane to the completion of the right-turn vehicle A's lane change.

The second object of the present invention is to provide a guidance system for vehicles turning right at a signal intersection adopted by the above-mentioned guidance method to overtake a vehicle. It is integrated with the traffic environment information collected by the roadside unit to enhance the perception range and realize the over-the-horizon perception of right-turning vehicles; combined with the collaborative driving of multiple vehicles within the range of the intersection entrance, and the design of the intelligent vehicle driving trajectory optimization strategy, dynamic Guide the overtaking driving behavior of right-turning vehicles, so as to achieve the goal of improving the efficiency of vehicle traffic at intersections.

The present invention provides a right-turning vehicle overtaking guidance system at a signalized intersection, comprising a roadside unit for collecting road traffic information in real time, a main control device and a vehicle-mounted unit connected to the roadside unit, and the roadside unit Communicate with the vehicle-mounted unit, send the data information collected by the vehicle equipped with the vehicle-mounted unit to the main control device in real time, and send the control instruction information of the main control device to the vehicle at the same time; the improvement is: the main control device includes data Storage module, data processing module, time recording module, time calculation module, dissipation time calculation module, signal light judgment module, traffic state detection module, lane change trajectory planning module, and control signal sending module;

Wherein, the data storage module is used to store the data collected by the roadside unit, including the road traffic information collected in real time by the roadside unit and the data transmitted from the vehicle-mounted unit;

The data processing module is used to fuse the image data and traffic flow data of multiple vehicles in the data storage module, and complete the target identification by extracting, detecting and classifying features;

The time recording module is used to record the time when the target vehicle reaches the detection range, and at the same time record the initial time of the phase signal light in a certain direction of traffic and the end time of the signal light, the end time of the signal light = the initial time of the signal light + the length of the signal light cycle; It consists of light and green light, and the green light cycle length includes the yellow light time; the recording time is recorded in the form of hours: minutes: seconds;

The time calculation module calculates the length of time for the vehicle to reach the designated position according to the distance from the vehicle to the designated position and its current speed; or, predicts the length of time for the vehicle to reach the designated position according to the expected travel trajectory of the vehicle and the current speed, and then records according to the time. The data recorded by the module calculates or predicts the time when the vehicle arrives at the specified location;

The dissipated time calculation module calculates the time for the queuing vehicles to dissipate at the intersection, and the calculation formula for the dissipated time of the queuing vehicles is as follows:

T _d =q*re /( _n *Sq)

In the formula: T _d is the queuing vehicle dissipation time, s; q is the vehicle arrival rate of the passing phase, pcu/h; r _e is the effective red light time of the passing phase, s; n is the number of lanes corresponding to the passing phase; S is the single vehicle Channel saturation flow rate, pcu/h;

The signal light judging module is used for judging the state of the signal light and the time node when the target vehicle reaches the designated position according to the result calculated by the time calculation module, the result calculated by the dissipation time calculation module, and the data recorded by the time recording module. When reaching the designated position, the turn-on time of the signal light is less than half of the perimeter of the signal light, which is the initial stage of the signal light, otherwise it belongs to the middle and late stage of the signal light;

The traffic state detection module includes an obstructing vehicle identification module and a risk assessment module; the obstructed vehicle identification module is used to determine whether the vehicle in front of the right-turning vehicle is an obstructing vehicle according to the results output by the time calculation module and the signal light judgment module. When the vehicle in front of the right-turning vehicle reaches the stop line, the signal light is red, which means that the vehicle is obstructing;

The risk assessment module is used to determine the potential field distribution of the overtaking vehicle changing lanes according to the road potential field model, and to evaluate the risk of the vehicle changing lanes according to the potential field distribution;

The lane-changing trajectory planning module, according to the assessment result of the risk assessment module, plans the vehicle lane-changing trajectory within the scope of the safety domain, if the potential field safety critical value is C, then the lane-changing trajectory planned by the vehicle A needs to satisfy E _S1 at the same time. <C and E _S2 < C, it can be regarded as driving within the safe range; E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoy of adjacent lanes when the right-turn vehicle changes lanes and overtakes; The lane trajectory planning module obtains the lane change trajectory of the vehicle and sends it to the roadside unit in real time through the control signal sending module, and the roadside unit transmits it to the on-board unit, and the on-board unit receives the signal and feeds it back to the vehicle control module;

The vehicle control module takes the trajectory line planned by the lane-changing trajectory planning module as a reference, and obtains the trajectory coordinates and vehicle speed of the lane-changing through online optimization, so as to complete the tracking of the reference trajectory.

As a preferred option of the present invention, the roadside unit adopts LTE-V/5G communication technology, including a high-gain directional beam control read-write antenna and a radio frequency controller; wherein, the high-gain directional beam control read-write antenna is a microwave transceiver module, Responsible for signal and data transmission/reception, modulation/demodulation, encoding/decoding, encryption/decryption; the radio frequency controller is the module that controls the transmission and reception of data and processes information sent and received to the upper computer;

The on-board unit is an OBU or OBD diagnostic terminal, and is a microwave device that uses the short-range communication network DSRC technology to communicate with on-board units of other vehicles;

The vehicle is a vehicle with a relatively high level of L4 autonomy, and two on-board cameras are set on the vehicle, which are placed in front of the vehicle and behind the vehicle respectively. The current road environment of the vehicle is recorded by the on-board cameras, and real-time image information around the vehicle is collected;

Millimeter-wave radars and lidars are installed on the vehicle; among them, 5 millimeter-wave radars are composed of a forward radar and four corner radars; 3 lidars are placed on the left, middle and right positions on the top of the vehicle; on-board cameras, The lidar signal and the millimeter-wave radar signal converted by the CAN card are jointly input into the industrial computer for perception and fusion, and the targets on the road are identified and tracked;

The working condition machine is used for target-level fusion of the information data perceived by the vehicle-mounted camera, the millimeter-wave radar and the lidar, and the information after fusion is transmitted to the roadside unit through the vehicle-mounted unit.

As a preference of the present invention, the road potential field model expression is as follows:

表示车辆A指向边界线j1的距离矢量；同理,

表示车辆A指向边界线j2的距离矢量，ρ为道路边界场系数。In the formula, E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoys of adjacent lanes when the right-turning vehicle changes lanes and overtaking, and the y-axis coordinate of the right-turning vehicle A at time _t is The boundary j1 and j2 axis coordinates of adjacent lanes are y _{s, j1} , y _{s, j2} ,

Represents the distance vector of vehicle A to the boundary line j1; in the same way,

represents the distance vector of the vehicle A pointing to the boundary line j2, and ρ is the road boundary field coefficient.

As a preferred embodiment of the present invention, the lane-changing trajectory expression is:

In the formula, x _t and y _t are the abscissa and ordinate values of the right-turning vehicle A at time t, Vt is the speed of the x-axis direction at time t, assuming a constant speed, w is the lane width, and t _f is the planning required for the vehicle to change lanes. time, usually t _f > 3s, which can ensure the stability when changing lanes;

As a preferred method of the present invention, the vehicle control module solves the trajectory coordinates and vehicle speed of the right-turning vehicle lane change as follows:

A nonlinear dynamic prediction model of vehicle motion is established, where L is the wheelbase of the own vehicle, and L _f is the distance from the center of mass to the foremost segment of the own vehicle; the state variables and control input of the own vehicle of the vehicle turning right and overtaking are X _t = [x _t , y _t , θ _t , v _t ] ^T and μ _t = [δ _t , at _t ] ^T , (x _t , y _t ) are the position coordinates of the vehicle at time t, and θ _t is the transverse direction of the vehicle at time t Swing angle, v _t is the speed of the vehicle at time t, δ _t is the steering angle of the front wheel at time t of the vehicle, and a _t is the acceleration of the vehicle at time t;

Divide the Th time step into N _p steps, and use the following formula to derive the kinematic state of the vehicle at step k+1 from the state at step k:

表示在总的时间步为p时，车辆t时刻第k+1步的横坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的纵坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的横摆角，

表示在总的时间步为p时，车辆t时刻第k+1步的速度；

定义同上，是第k步的量，

表示在总的时间步为p时，车辆t时刻第k步的加速度；Th为右转车辆A在初始车道准备换道开始至右转车辆A换道完成的消耗时间。where:

represents the abscissa of the k+1th step at time t of the vehicle when the total time step is p,

represents the ordinate of the k+1th step at time t of the vehicle when the total time step is p,

represents the yaw angle of the k+1th step at time t of the vehicle when the total time step is p,

Indicates the speed of the k+1th step of the vehicle at time t when the total time step is p;

The definition is the same as above, it is the amount of the kth step,

When the total time step is p, the acceleration of the k-th step of the vehicle at time t; Th is the elapsed time from the start of the right-turn vehicle A preparing to change lanes in the initial lane to the completion of the right-turn vehicle A's lane change.

The advantages and positive effects of the present invention are:

1. The present invention integrates intersection signal information, vehicle line-of-sight information collected by on-board sensing equipment, and traffic environment information collected by roadside units to enhance the perception range and realize over-the-horizon perception of right-turning vehicles. Vehicle-road information fusion perception has the advantages of low latency, wide coverage, and high data accuracy.

2. The present invention is based on the Internet of Vehicles technology, perceives the road environment at the intersection in real time, combines the collaborative driving of multiple vehicles within the entrance road of the intersection, and the design of the intelligent vehicle driving trajectory optimization strategy, dynamically guides the overtaking driving behavior of right-turning vehicles, reduces the Increase the efficiency of crossing traffic due to delays caused by bus obstruction.

3. The guidance method provided by the present invention guides the social vehicles turning right to drive into the lanes after the "increase". Compared with the traditional fixed lane division method, on the one hand, the virtual lane form combines the characteristics of the small lateral swing of the intelligent vehicle. , making full use of the existing lane resources and avoiding the waste of road resources due to the setting of fixed lane facilities; on the other hand, the virtual lane is flexible and flexible, and responds to the overtaking needs of right-turning vehicles in real time.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only It is an embodiment of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to the provided drawings without creative work.

1 is a schematic structural diagram of a right-turn vehicle overtaking guidance system at an intersection according to Embodiment 1 of the present invention;

2 is a schematic flowchart of a method for guiding a vehicle turning right at an intersection to overtake a vehicle according to Embodiment 2 of the present invention;

Fig. 3 is one of the scene schematic diagrams of the overtaking guidance method for a right-turning vehicle at an intersection according to the present invention;

Fig. 4 is the second schematic diagram of the scene of the present invention of the method for guiding a vehicle turning right at an intersection to overtake;

5 is a schematic diagram of the overtaking trajectory of a right-turning vehicle changing lanes according to the method for guiding a right-turning vehicle to overtake at an intersection according to the present invention;

Fig. 6 is the dissipation diagram of the queued vehicles at the intersection.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

Example 1

Referring to FIG. 1 , the present invention provides a system for guiding vehicles turning right at signalized intersections to overtake vehicles. The system includes a roadside unit 1 (RSU, Road Side Unit) for collecting road traffic information in real time, and a roadside unit. 1. The connected main control device 3 and the on-board unit 2, the roadside unit 1 uses the LTE-V/5G communication technology to communicate with the on-board unit 2, and sends the data information collected by the vehicle equipped with the on-board unit 2 to the main control in real time. device 3, and at the same time send the control instruction information of the main control device 3 to the vehicle equipped with the on-board unit 2 to meet the needs of vehicle-road coordination.

The design of the roadside unit 1 in this embodiment follows the national standard GB20851, the communication frequency is 5.8GHz, and the information transmission coverage is 300m; the roadside unit RSU includes a high-gain directional beam control read-write antenna and a radio frequency controller; wherein , The high-gain directional beam control read-write antenna is a microwave transceiver module, responsible for signal and data transmission/reception, modulation/demodulation, encoding/decoding, encryption/decryption; the radio frequency controller is to control the transmission and reception of data and the processing of upper-level A module for sending and receiving information;

The on-board unit 2 is an OBU (On Board Unit) or OBD (On Board Diagnostic) diagnostic terminal, and is a microwave device that uses the Dedicated Short Range Communication (DSRC) technology to communicate with on-board units of other vehicles.

The vehicle guided in this embodiment is a vehicle with a high level of autonomy (L4 level), and the vehicle is equipped with necessary sensing equipment. The sensing equipment of the vehicle includes an on-board camera 4 and a radar sensing equipment 5 (radar sensor). The information is fused in the working condition machine 6, and the fused information is transmitted to the roadside unit 1 through the on-board unit 2. The roadside unit 1 will collect the information of multiple on-board units 2, and feed the information back to the main control device 3. The main control device 3 performs information fusion to enhance perception. Finally, the main control device 3 feeds back the lane-changing trajectory of the vehicle obtained by the lane-changing trajectory planning module to the vehicle through the communication network, and the vehicle outputs the optimal driving route through the vehicle control module 7 .

Continuing to refer to FIG. 1, the main control device 3 in this embodiment includes a data storage module 31, a data processing module 32, a time recording module 33, a time calculation module 34, a dissipation time calculation module 35, a signal light judgment module 36, and a traffic state detection module. Module 37, lane change trajectory planning module 38, control signal sending module 39;

Wherein, the data storage module 31 is used to store the data collected by the roadside unit 1, including the road traffic information collected in real time by the roadside unit 1 and the data transmitted from the vehicle-mounted unit 2;

The data processing module 32 is used to fuse the image data and traffic flow data of a plurality of vehicles in the data storage module 31, and complete the identification of the target through feature extraction, detection and classification;

The time recording module 33 is used to record the time when the target vehicle arrives within the detection range, and at the same time record the initial moment of the phase signal light in a certain direction of traffic and the end time of the signal light, the end time of the signal light=the initial moment of the signal light+the cycle length of the signal light; the signal light is composed of It consists of red light and green light, and the length of the green light cycle includes the length of the yellow light; the recording time is recorded in the form of hours: minutes: seconds;

The time calculation module 34 calculates the duration of the vehicle reaching the specified position according to the distance from the vehicle to the specified position and its current speed; Record the data recorded by the module, calculate or predict the time when the vehicle arrives at the specified location;

The dissipated time calculation module 35 calculates the length of time for the queuing vehicles at the intersection to dissipate.

T _d =q*re /( _n *Sq)

In the formula: T _d is the queuing vehicle dissipation time, s; q is the vehicle arrival rate of the passing phase, pcu/h; r _e is the effective red light time of the passing phase, s; n is the number of lanes corresponding to the passing phase; S is the single vehicle Channel saturation flow rate, pcu/h;

The signal light judging module 36 is used to judge the state of the signal light and the time node when the target vehicle arrives at the designated position according to the result calculated by the time calculation module 34, the result calculated by the dissipation time calculation module 35, and the data recorded by the time recording module 33. , if the target vehicle arrives at the designated position, and the turn-on time of the signal light is less than half of the perimeter of the signal light, it is the initial stage of the signal light, otherwise it belongs to the middle and late stage of the signal light;

The traffic state detection module 37 includes an obstructing vehicle identification module 371 and a risk assessment module 372;

The obstructing vehicle identification module 371 is used to determine whether the vehicle in front of the right-turning vehicle is an obstructing vehicle according to the results output by the time calculation module 34 and the signal light judging module 36, and if the vehicle in front of the right-turning vehicle reaches the stop line, the signal light is red. lights, to obstruct the vehicle;

The risk assessment module 372 is configured to determine the potential field distribution of the overtaking vehicle changing lanes according to the road potential field model, and to evaluate the risk of the vehicle changing lanes according to the potential field distribution;

The lane-changing trajectory planning module 38, according to the evaluation result of the risk assessment module 372, plans the lane-changing trajectory of the vehicle within the scope of the safety zone; the lane-changing trajectory planning module 38 obtains the planned lane-changing trajectory of the vehicle through the control signal sending module 39 It is sent to the roadside unit 1 in real time, and transmitted to the vehicle-mounted unit 2 through LTE-V/5G communication, and the vehicle-mounted unit 2 receives the signal and feeds it back to the vehicle control module 7 of the vehicle A;

The vehicle control module 7, taking the planned trajectory line as a reference, obtains the trajectory coordinates and vehicle speed of the lane change through online optimization, completes the tracking of the reference trajectory, and ensures that the vehicle can keep safe driving within the speed limit of 60km/h, and It can ensure the user's riding experience in the process of safe steering.

In this embodiment, the collection of traffic information can be divided into the vehicle side and the road side, and the information on the vehicle side is mainly collected by the sensing device equipped on the vehicle, which is used to assist the vehicle in changing lanes and overtaking. The roadside first collects road vehicle information within the communication range (300m) of the roadside unit (traffic flow information in the rightmost lane, including the speed and position information of buses and social vehicles), which is processed in the data processing module 32. Data fusion, mainly to identify and track the moving road environment (traffic participants such as vehicles and pedestrians).

Further, the vehicle described in this embodiment is provided with two on-board cameras 4, which are respectively placed in front of the vehicle and behind the vehicle. The on-board cameras can record the current road environment of the vehicle and collect real-time image information around the vehicle;

The radar sensing device 5 is a kind of external sensor of the intelligent vehicle, which can be divided into ultrasonic radar, millimeter-wave radar, laser radar, etc., and the principles of different radars are different. The invention is mainly used to detect the distance, speed, angle and other information of lane lines, other vehicles, pedestrians, bicycles and other objects, and can be equipped with millimeter wave radar and laser radar on the vehicle; It consists of forward radar and four corner radars; 3 lidars are placed on the left, middle and right positions on the top of the vehicle; vehicle camera 4, lidar signals and millimeter-wave radar signals converted by CAN card are jointly input to the industrial computer 6 Perceptual fusion is carried out in the process, and the target on the road is identified and tracked;

The working condition machine 6 is mainly used to perform target-level fusion of the information data perceived by the on-board camera, millimeter-wave radar and lidar, and output the information of other vehicles, obstacle positions, speeds and other information in the vehicle vision. It is transmitted to the roadside unit 1 through the on-board unit 2, and is provided by the roadside unit 1 to the main control device 3 for decision analysis.

In addition, considering that in the process of vehicle driving path planning, the most important thing is to avoid accidents such as collision with other vehicles. Therefore, in the process of vehicle driving path planning, it is necessary to obtain a feasible set of vehicle lane changing trajectories within the scope of the safety domain. .

In this embodiment, when a right-turning vehicle A changes lanes to pass the intersection ahead of time, the vehicles in front of the adjacent lanes of vehicle A are in a static avoidance state, so it can be regarded as a static obstacle, and multiple vehicles are in a static queue state, forming a static state. The convoy can be regarded as a boundary line. This boundary line is to be avoided by the vehicle A during the lane change process, and the collision risk increases as the distance between the right-turning vehicle A and the boundary line decreases. Therefore, the risk assessment module 372 The road potential field model can be used for reference to outline the safety field of vehicle A. The model expression is as follows:

表示车辆A指向边界线j1的距离矢量；同理，

表示方向为车辆A指向边界线j2的距离矢量，ρ为道路边界场系数。In the formula, E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoys of the adjacent lanes of car A. Assuming that the y-axis coordinate of vehicle A at time t is y _t , the boundary j1 of the adjacent lane of car A is equal to The j2 axis coordinates are y _{s, j1} , y _{s, j2} ,

Represents the distance vector of vehicle A pointing to the boundary line j1; in the same way,

Represents the distance vector whose direction is that the vehicle A points to the boundary line j2, and ρ is the road boundary field coefficient.

Based on the calculation of the potential field, the distribution of the potential field is clearly expressed in Figure 5. The color depth represents the strength and weakness relationship of the safety potential field. The darker the color, the greater the strength of the safety potential field and the higher the road traffic safety risk. Suppose the safety critical value of the potential field is C, then the lane-changing trajectory planned by the vehicle A needs to satisfy the conditions of E _S1 <C and E _S2 <C at the same time;

When the lane-changing trajectory planning module plans the vehicle lane-changing trajectory, the most commonly used method is to describe it with a quintic polynomial. Through the derivation of the quintic polynomial, the lane-changing trajectory expression can be obtained as:

In the formula, x _t , y _t are the abscissa and ordinate values of the vehicle at time t, V is the lateral speed of the vehicle (speed in the x-axis direction), assuming that the lateral speed of the vehicle remains unchanged (uniform speed) during the lane change process, w is the lane width, t _f is the planning time required for the vehicle to change lanes, usually t _f >3s, which can ensure the stability of the lane change.

Further, the main purpose of the vehicle control module 7 in this embodiment is based on the trajectory planned by the lane-changing trajectory planning module as a reference, and the vehicle continuously adjusts the lateral position, cruising speed and acceleration of the vehicle while meeting the objectives of safety and comfort. Equal physical quantities, and online optimization to solve the desired trajectory coordinates and vehicle speed of lane change through MPC and other methods, until the tracking of the reference trajectory is completed. The elapsed time from the time when the right-turning vehicle is ready to change lanes in the initial lane to the completion of the vehicle lane changing is Th.

In this embodiment, a nonlinear dynamic prediction model of vehicle motion is established, where L is the wheelbase of the ego vehicle, L _f is the distance from the center of mass to the foremost segment of the ego car, and the state variables and control input of the ego car of a vehicle turning right and overtaking are: X _t = [x _t , y _t , θ _t , v _t ] ^T and μ _t = [δ _t , at _t ] ^T , (x _t , y _t ) are the position coordinates of the vehicle at time t, and θ _t is the vehicle t The yaw angle at time, v _t is the speed of the vehicle at time t, δ _t is the steering angle of the front wheel at time _t of the vehicle, and at is the acceleration of the vehicle at time t; at the same time, the position and control input of the surrounding vehicles are also obtained separately, expressed as :

Divide the Th time step into N _p steps, then the kinematic state of the vehicle at step k+1 can be derived from the state at step k:

表示在总的时间步为p时，车辆t时刻第k+1步的横坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的纵坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的横摆角，

表示在总的时间步为p时，车辆t时刻第k+1步的速度；

定义同上，是第k步的量，

表示在总的时间步为p时，车辆t时刻第k步的加速度。where:

represents the abscissa of the k+1th step at time t of the vehicle when the total time step is p,

represents the ordinate of the k+1th step at time t of the vehicle when the total time step is p,

represents the yaw angle of the k+1th step at time t of the vehicle when the total time step is p,

Indicates the speed of the k+1th step of the vehicle at time t when the total time step is p;

The definition is the same as above, it is the amount of the kth step,

Represents the acceleration of the k-th step at time t of the vehicle when the total time step is p.

Example 2

This embodiment provides a method for guiding vehicles turning right at a signalized intersection to overtake. For the intersection as shown in FIG. 3, taking the entrance road from west to east as an example, the right lane is surrounded by buses and ordinary vehicles. It is assumed that the driving direction of all buses arriving at the intersection is straight, and the driving direction of other ordinary vehicles is straight or right. The waiting time of vehicle A, guide the vehicle in front of it and the vehicle in its adjacent lane to automatically move closer to the lane line, so that the original two lanes are divided by the red virtual lane line, "increased" to "three lanes", and then the vehicle A Change lanes to the "increased" lane, pass the bus, and turn right.

In this embodiment, the traffic flow information of the rightmost lane is collected by the roadside unit, including the speed and position information of buses and social vehicles; the composition of traffic flow, that is, the identification of buses and ordinary social vehicles; In the environment, the steering information of the vehicle can be obtained in advance, so whether the vehicle behind the bus is a right-turn vehicle can be identified in advance.

Assuming that the intersection shown in Figure 3 is a standard intersection, it is divided into north-south direction and east-west direction. The green light (including yellow light) of the east-west phase is L1, the red light is R1, and the green light (including yellow light) of the north-south phase is long. ) is L2 and the red light is R2, then according to the signal timing rule L1+R1=L2+R2.

In this embodiment, the driving direction is from west to east. When the vehicle reaches the stop line at the intersection, it generally corresponds to two signal states of red light and green light (including yellow light). Under different signal states, the passing process of the vehicle And the impact on other vehicles is not the same.

Based on this, the present embodiment provides a method for guiding a vehicle turning right at a signalized intersection to overtake a vehicle. The specific process is shown in FIG. 2 , including the following steps:

Step S1, assuming that 100m from the stop line is the detection range, the roadside unit detects the arrival of the right-turn vehicle A followed by the bus in the right lane, and the time when the right-turn vehicle A arrives within the detection range is T1 (assuming it is 09: 00:00);

Step S2, determine whether the status of the signal light at time T1 is green; if so, go to step S3; if not, go to step S15;

In step S3, when the vehicle A turning right is detected, and it is judged that the status of the signal light is green at this time, there will be two situations: (1) in the middle and late stages of the green light, the queued vehicles in front of the vehicle A have dissipated; (2) in the early stage of the green light , there are still unreleased queuing vehicles before the stop line; if it is the first situation, then go to step S4; if it is the second situation, go to step S8;

Step S4, according to the current distance LA of the right-turn vehicle A from the stop line and the current speed V, predict the time length Ty (unit s) required to reach the stop line, Ty=LA/V, then the right-turn lane A reaches the stop line. Time is T1+Ty;

Step S5: Assume that the initial time when the green light of the east-west phase is turned on is T0, and the green light end time is calculated according to the length of the green light cycle to be T0+L1. Judge T0+L1>T1+Ty? If yes, it means that the vehicle can pass normally in the green light phase, and go to step S6; if no, it means that the vehicle cannot reach the stop line in the green light phase, and go to step S7;

Step S6, the roadside unit sends the guidance information to the vehicle-mounted unit of the right-turning vehicle A to guide the right-turning vehicle A to accelerate through;

Step S7, the traffic state detection module 33 detects the obstructing vehicles in front of the right-turning vehicle A; assuming that the vehicles in front of A are driving at a uniform speed, taking the lane where A is located as an example, the vehicles in front of A are B1, B2... , identify the distances LB1, LB2... from B1, B2... to the stop line, and their current speeds VB1, VB2..., so according to the distance formula, we can get the time for B1, B2... to pass the stop respectively as TB1, TB2...; Take car B1 as an example, calculate the time for B1 to pass the stop line as T1+TB1, compare it with the end time of the green light phase, and judge whether T0+L1>T1+TB1? If yes, it means that B1 car can pass normally; if not, it means that it cannot pass; and so on, judge the information of the lane where car A is and other vehicles in front of A in the adjacent lane of car A, according to this, identify when the green light phase ends, Obstructing vehicles Z1, Z2... located in front of the same lane of vehicle A and obstructing vehicles C1, C2... in front of the adjacent lane of vehicle A;

Step S8, calculate the time Td when the queued vehicles are dissipated, and the dissipation diagram of the queued vehicles at the intersection is shown in Figure 6, and the specific calculation method is as follows:

The time required for the vehicles queued in front of the stop line to dissipate is mainly determined by the vehicle arrival rate, the saturation flow rate and the length of the red light. The calculation formula is as follows:

q*(r _e +T _d )=n*S*T _d

Through formula conversion, the calculation formula of the dissipation time of queuing vehicles can be obtained as follows:

T _d =q*re /( _n *Sq)

In the formula: T _d - queuing vehicle dissipation time, s; q - vehicle arrival rate of the passing phase, pcu/h; r _e - effective red light time of the passing phase, s; n - the number of lanes corresponding to the passing phase; S - single vehicle Channel saturation flow rate, pcu/h;

Step S9, judge T0+L1>T0+Td+Ty? If yes, it indicates that the right-turning vehicle A can still reach the stop line after the queued vehicles in the previous signal cycle are dissipated, then go to step S6; if not, it indicates that the queued vehicles in the previous cycle cannot completely dissipate, then go to step S7;

Step S10, in order to ensure that the right-turning overtaking vehicle A does not affect the normal driving vehicle in this direction, the overtaking vehicle should complete before the end of the red light period of this phase, and read the time Tg=T0+L1+R1 when the red light of this phase ends;

Step S11, according to the current distance between the right-turn vehicle A and the stop line, predict that the time for the right-turn vehicle A to travel through the stop line according to the expected overtaking trajectory line is Tw;

Tw=Th+Tf

Tf=Lb/V

In the formula, Th is the time required for the right-turning vehicle A to change lanes, and its value ranges from 3s to 8s, Tf is the time to travel to the stop line after changing lanes, and Lb is the virtual time after the right-turning vehicle A changes lanes to increase. The distance from the back of the lane to the stop line, V is the speed of the right-turn vehicle A;

Step S12, determine whether T1+Tw>Tg? If no, it indicates that the vehicle can complete the right turn before the end of the red light period of this phase, then go to step S13; if yes, it indicates that it is not feasible, then go to step S15;

Step S13, the main control device sends guidance information to the obstructing vehicles Z1, Z2... in front of the same lane of vehicle A and the vehicles C1, C2... drive;

Step S14, the main control device guides the right-turning vehicle A to overtake and drive right-turning;

Step S15, the roadside equipment sends guidance information to the vehicle-mounted unit of the vehicle A turning right to guide the vehicle A to decelerate.

In this embodiment, the planning method of the expected overtaking trajectory line of the right-turning vehicle A in step S11 is as follows;

In the formula, x _t , y _t are the abscissa and ordinate values of the right-turning vehicle A at time t, V is the lateral speed of the vehicle A, assuming that the lateral speed of the vehicle remains unchanged during the lane changing process, w is the lane width, t _f The planning time required for the vehicle to change lanes, usually t _f >3s, can ensure the stability when changing lanes.

In step S14, when the right-turning vehicle A changes lanes, the risk assessment module in the main control device needs to determine the potential field distribution of the lane-changing overtaking vehicle A according to the road potential field model, so as to evaluate the risk of the vehicle changing lanes. Obtain a feasible set of vehicle lane-changing trajectories within the range; if the potential field safety critical value is C, then the planned expected overtaking trajectory line when the right-turning vehicle A overtakes through the lane needs to satisfy the conditions of E _S1 <C and E _S2 <C at the same time, can be regarded as driving within a safe range; wherein, the road potential field model is expressed as follows:

表示右转车辆A指向边界线j1的距离矢量；同理，

表示右转车辆A指向边界线j2的距离矢量，ρ为道路边界场系数。In the formula, E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoys of adjacent lanes when the right-turning vehicle A changes lanes to overtake, and the y-axis coordinate of the right-turning vehicle A at time t is y _t , A The axis coordinates of the boundary j1 and j2 of the adjacent lanes of the vehicle are y _{s, j1} , y _{s, j2} ,

represents the distance vector of the right-turning vehicle A pointing to the boundary line j1; similarly,

It represents the distance vector of the right-turning vehicle A pointing to the boundary line j2, and ρ is the road boundary field coefficient.

Further, in step S14, the specific way that the main control device guides the right-turning vehicle A to overtake and turn right is as follows: the main control device first passes the vehicle lane-changing trajectory planned by the lane-changing trajectory planning module within the scope of the safety zone through the control signal sending module. It is sent to the roadside unit in real time, and the roadside unit transmits it to the on-board unit through LTE-V/5G communication. After receiving the signal, the on-board unit feeds back to the vehicle control module of the right-turning vehicle A. The online optimization solves the trajectory coordinates and vehicle speed of the right-turning vehicle A changing lanes.

Further, the vehicle control module solves the trajectory coordinates and vehicle speed of the right-turning vehicle A for lane changing as follows:

A nonlinear dynamic prediction model of vehicle motion is established, where L is the wheelbase of the own vehicle, and L _f is the distance from the center of mass to the foremost segment of the own vehicle; the state variables and control input of the own vehicle of the vehicle turning right and overtaking are X _t = [x _t , y _t , θ _t , v _t ] ^T and μ _t = [δ _t , at _t ] ^T , (x _t , y _t ) are the position coordinates of the vehicle at time t, and θ _t is the transverse direction of the vehicle at time t Swing angle, v _t is the speed of the vehicle at time t, δ _t is the steering angle of the front wheel at time t of the vehicle, and a _t is the acceleration of the vehicle at time t;

Divide the Th time step into N _p steps, and use the following formula to derive the kinematic state of the vehicle at step k+1 from the state at step k:

表示在总的时间步为p时，车辆t时刻第k+1步的横坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的纵坐标，

表示在总的时间步为p时，车辆t时刻第k+1步的横摆角，

表示在总的时间步为p时，车辆t时刻第k+1步的速度；

定义同上，是第k步的量，

表示在总的时间步为p时，车辆t时刻第k步的加速度；Th为右转车辆A在初始车道准备换道开始至右转车辆A换道完成用消耗时间。where:

represents the abscissa of the k+1th step at time t of the vehicle when the total time step is p,

represents the ordinate of the k+1th step at time t of the vehicle when the total time step is p,

represents the yaw angle of the k+1th step at time t of the vehicle when the total time step is p,

Indicates the speed of the k+1th step of the vehicle at time t when the total time step is p;

The definition is the same as above, it is the amount of the kth step,

When the total time step is p, the acceleration of the vehicle at the k-th step at time t; Th is the elapsed time from the start of the right-turn vehicle A preparing to change lanes in the initial lane to the completion of the right-turn vehicle A's lane change.

The lateral control system of an autonomous vehicle can track the path and curvature of the output of the control system to reduce tracking errors and ensure vehicle stability and comfort. At present, there are many methods used in the lateral control of autonomous vehicles: preview control, PID control, adaptive control, synovial control, fuzzy control, and model predictive control. The lateral control of the vehicle can keep the maximum lateral deviation below 0.4 meters when the vehicle is traveling in a straight line (speeds less than 110 km/h).

The width of existing cars is generally between 1.6m and 1.8m, and the width of large vehicles such as general buses is 2.05m. According to the national standard GB50647-2011 "Planning Specifications for Urban Road Intersections", the average planning width of a lane is 3.0 to 3.75.

As shown in Figure 4, assuming that the width of a single road is 3.75m, the bus is 2.05m, the ordinary vehicle is 1.8m, and the distance between the vehicle and the edge of the lane line is ≥0.4m, then the distance between vehicles is 0.525m>0.4m, considering In terms of the stability of lateral control in a moving environment, and with the improvement of vehicle lateral control accuracy, it can be determined that the guidance method provided in this embodiment is feasible in an urban road environment, and can save road land resources while improving the efficiency of intersection traffic.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, but not to limit them; although the embodiments of the present invention have been described in detail with reference to the foregoing embodiments, those skilled in the art It should be understood that: it is still possible to modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements to some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the embodiments of the present invention scope of the programme.

Claims (10)

1. a right-turn vehicle at a signalized intersection is characterized in that, the method comprises the following steps: Step S1, set the detection range within a certain distance from the stop line, the roadside unit detects the arrival of the right-turn vehicle A followed by the bus in the right lane, and record the time when the right-turn vehicle A arrives within the detection range as T1; Step S2, determine whether the status of the signal light at time T1 is green; if so, go to step S3; if not, go to step S15; Step S3, judging the time point of the status of the green light signal; if it is in the middle and late stages of the green light, and the queued vehicles in front of the right-turning vehicle A have dissipated, then go to step S4; if it is the early green light, there is still unreleased before the stop line queuing vehicles, then go to step S8; Step S4, according to the current distance LA and the current speed V of the right-turn vehicle A from the stop line, predict the time length Ty required to reach the stop line, Ty=LA/V, then the time when the right-turn vehicle A arrives at the stop line is T1+Ty ; Step S5: Set the initial time of turning on the green light of the traffic direction phase to be T0, the length of the green light cycle to be L1, the length of the red light cycle to be R1, and to calculate the end time of the green light phase according to the length of the green light cycle as T0+L1, and determine T0+L1>T1+Ty ? If yes, it indicates that the right-turning vehicle A can pass normally within the green light phase, then go to step S6; if no, it indicates that the right-turning vehicle A cannot reach the stop line within the green light phase, then go to step S7; Step S6, the roadside unit sends the guidance information to the vehicle-mounted unit of the right-turning vehicle A to guide the right-turning vehicle A to accelerate through; Step S7: The traffic state detection module detects the vehicles in front of the right-turning vehicle A, and determines the obstructing vehicles Z1, Z2... in front of the same lane of the right-turning vehicle A and the obstructing vehicles C1, C2... in front of the adjacent lanes of the right-turning vehicle A. ; When determining an obstructing vehicle, according to the distance of each vehicle in front of the right-turning vehicle A from the stop line and its current speed, calculate the length of each vehicle passing through the stop line, and determine the length of each vehicle passing the stop line according to the length of each vehicle passing the stop line. The time when the green light phase ends T0+L1 > the time when the vehicle in front of the right-turning vehicle A passes the stop line? If it is, it means that the vehicle in front of the right-turning vehicle A can pass normally; if not, it means that the vehicle in front of the right-turning vehicle A cannot pass, which is an obstacle to the vehicle; Step S8, calculate the time length Td for the queuing vehicle to dissipate, and the calculation formula of the queuing vehicle dissipation time length is as follows: T _d =q*re /( _n *Sq) In the formula: T _d is the queuing vehicle dissipation time, s; q is the vehicle arrival rate of the passing phase, pcu/h; r _e is the effective red light time of the passing phase, s; n is the number of lanes corresponding to the passing phase; S is the single vehicle Channel saturation flow rate, pcu/h; Step S9, judge T0+L1>T0+Td+Ty? If yes, it indicates that the right-turning vehicle A can still reach the stop line after the queued vehicles in the previous signal cycle are dissipated, then go to step S6; if not, it indicates that the queued vehicles in the previous cycle cannot completely dissipate, then go to step S7; Step S10: In order to ensure that the right-turning vehicle A overtaking does not affect the normal driving vehicles in this direction, the right-turning overtaking vehicle A should be completed before the end of the red light period of this phase, and read the time Tg=T0+ when the red light of this phase ends. L1+R1; Step S11, according to the current distance between the right-turning vehicle A and the stop line, predict the duration Tw of the right-turning vehicle A traveling to the stop line according to the expected overtaking trajectory line; Tw=Th+Tf Tf=Lb/V In the formula, Th is the time required for the right-turning vehicle A to change lanes, and its value ranges from 3s to 8s, Tf is the time to travel to the stop line after changing lanes, and Lb is the virtual time after the right-turning vehicle A changes lanes to increase. The distance from the back of the lane to the stop line, V is the speed of the right-turn vehicle A; Step S12, determine whether T1+Tw>Tg? If no, it indicates that the vehicle can complete the right turn before the end of the red light period of this phase, then go to step S13; if yes, it indicates that it is not feasible, then go to step S15; Step S13, the main control device sends guidance information to the obstructing vehicles Z1, Z2... in front of the same lane of the right-turning vehicle A and the vehicles C1, C2... in front of the adjacent lane of the right-turning vehicle A, so as to guide the obstructing vehicles to approach the lane edge line to decelerate drive; Step S14, the main control device guides the right-turning vehicle A to overtake and drive right-turning; Step S15 , the roadside unit sends guidance information to the vehicle-mounted unit of the right-turning vehicle A to guide the right-turning vehicle A to decelerate. 2. The guiding method according to claim 1, wherein in step S11, the planning method of the expected overtaking trajectory line of the right-turning vehicle A is as follows;

In the formula, x _t , y _t are the abscissa and ordinate values of the right-turning vehicle A at time t, Vt is the speed of the x-axis direction at time t, w is the lane width, t _f is the planning time required for the vehicle to change lanes, usually t _f > 3s. 3. The guiding method according to claim 1, characterized in that, when the right-turn vehicle A changes lanes in step S14, the risk assessment module in the main control device needs to determine the potential field of the lane-changing overtaking vehicle according to the road potential field model. distribution, so as to assess the risk of vehicle lane changing, and obtain a feasible set of vehicle lane changing trajectories within the scope of the safety domain; if the potential field safety critical value is C, then the expected overtaking trajectory planned by the right-turning vehicle A when overtaking Only if the conditions of E _s1 <C and E _s2 <C are satisfied at the same time, it can be regarded as driving within the safe range; wherein, the road potential field model expression is as follows:

In the formula, E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoys of adjacent lanes when the right-turning vehicle A changes lanes to overtake, and the y-axis coordinate of the right-turning vehicle A at time t is y _t , A The boundary j1 and j2 axes of the adjacent lanes of the vehicle are y _{s, j1} , y _{s, j2} ,

Represents the distance vector of the right-turning vehicle A pointing to the boundary line j1; in the same way,

It represents the distance vector of the right-turning vehicle A pointing to the boundary line j2, and ρ is the road boundary field coefficient. 4. The guiding method according to claim 1, wherein in step S14, the specific mode that the main control device guides the right-turning vehicle A to overtake and drive right-turning is: The planned vehicle lane change trajectory is sent to the roadside unit in real time through the control signal sending module, and the roadside unit is transmitted to the vehicle-mounted unit through LTE-V/5G communication. The control module, the vehicle control module takes the planned trajectory line as a reference, and solves the trajectory coordinates and vehicle speed of the right-turning vehicle A changing lanes through online optimization. 5. Guidance method according to claim 4, is characterized in that, the mode that vehicle control module solves the trajectory coordinates and vehicle speed of right-turning vehicle A changing lanes is as follows: A nonlinear dynamic prediction model of vehicle motion is established, where L is the wheelbase of the own vehicle, and L _f is the distance from the center of mass to the foremost segment of the own vehicle; the state variables and control input of the own vehicle of the vehicle turning right and overtaking are X _t = [x _t , y _t , θ _t , v _t ] ^T and μ _t = [δ _t , at _t ] ^T , (x _t , y _t ) are the position coordinates of the vehicle at time t, and θ _t is the transverse direction of the vehicle at time t Swing angle, v _t is the speed of the vehicle at time t, δ _t is the steering angle of the front wheel at time t of the vehicle, and a _t is the acceleration of the vehicle at time t; Divide the Th time step into N _p steps, and use the following formula to derive the kinematic state of the vehicle at step k+1 from the state at step k:

where:

represents the abscissa of the k+1th step at time t of the vehicle when the total time step is p,

represents the ordinate of the k+1th step at time t of the vehicle when the total time step is p,

represents the yaw angle of the k+1th step at time t of the vehicle when the total time step is p,

Indicates the speed of the k+1th step of the vehicle at time t when the total time step is p;

The definition is the same as above, it is the amount of the kth step,

When the total time step is p, the acceleration of the vehicle at the k-th step at time t; Th is the elapsed time from the start of the right-turn vehicle A preparing to change lanes in the initial lane to the completion of the right-turn vehicle A's lane change. 6. A right-turning vehicle at a signal intersection overtaking driving guidance system, the system comprises a roadside unit for collecting road traffic information in real time, a main control device and a vehicle-mounted unit connected with the roadside unit, the roadside unit It communicates with the vehicle-mounted unit, sends the data information collected by the vehicle equipped with the vehicle-mounted unit to the main control device in real time, and simultaneously sends the control instruction information of the main control device to the vehicle; it is characterized in that: the main control device includes a data storage module , data processing module, time recording module, time calculation module, dissipation time calculation module, signal light judgment module, traffic state detection module, lane change trajectory planning module, control signal transmission module; Wherein, the data storage module is used to store the data collected by the roadside unit, including the road traffic information collected in real time by the roadside unit and the data transmitted from the vehicle-mounted unit; The data processing module is used to fuse the image data and traffic flow data of multiple vehicles in the data storage module, and complete the target identification by extracting, detecting and classifying features; The time recording module is used to record the time when the target vehicle reaches the detection range, and at the same time record the initial time of the phase signal light in a certain direction of traffic and the end time of the signal light, the end time of the signal light = the initial time of the signal light + the length of the signal light cycle; It consists of light and green light, and the green light cycle length includes the yellow light time; the recording time is recorded in the form of hours: minutes: seconds; The time calculation module calculates the length of time for the vehicle to reach the designated position according to the distance from the vehicle to the designated position and its current speed; or, predicts the length of time for the vehicle to reach the designated position according to the expected travel trajectory of the vehicle and the current speed, and then records according to the time. The data recorded by the module calculates or predicts the time when the vehicle arrives at the specified location; The dissipated time calculation module calculates the time for the queuing vehicles to dissipate at the intersection, and the calculation formula for the dissipated time of the queuing vehicles is as follows: T _d =q*re /( _n *Sq) In the formula: T _d is the queuing vehicle dissipation time, s; q is the vehicle arrival rate of the passing phase, pcu/h; r _e is the effective red light time of the passing phase, s; n is the number of lanes corresponding to the passing phase; S is the single vehicle Channel saturation flow rate, pcu/h; The signal light judging module is used for judging the state of the signal light and the time node when the target vehicle reaches the designated position according to the result calculated by the time calculation module, the result calculated by the dissipation time calculation module, and the data recorded by the time recording module. When reaching the designated position, the turn-on time of the signal light is less than half of the perimeter of the signal light, which is the initial stage of the signal light, otherwise it belongs to the middle and late stage of the signal light; The traffic state detection module includes an obstructing vehicle identification module and a risk assessment module; the obstructed vehicle identification module is used to determine whether the vehicle in front of the right-turning vehicle is an obstructing vehicle according to the results output by the time calculation module and the signal light judgment module. When the vehicle in front of the right-turning vehicle reaches the stop line, the signal light is red, which means that the vehicle is obstructing; The risk assessment module is used to determine the potential field distribution of the overtaking vehicle changing lanes according to the road potential field model, and to evaluate the risk of the vehicle changing lanes according to the potential field distribution; The lane-changing trajectory planning module, according to the assessment result of the risk assessment module, plans the vehicle lane-changing trajectory within the scope of the safety domain, if the potential field safety critical value is C, then the lane-changing trajectory planned by the vehicle A needs to satisfy E _S1 at the same time. <C and E _S2 < C, it can be regarded as driving within the safe range; E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoy of adjacent lanes when the right-turn vehicle changes lanes and overtakes; The lane trajectory planning module obtains the lane change trajectory of the vehicle and sends it to the roadside unit in real time through the control signal sending module, and the roadside unit transmits it to the on-board unit, and the on-board unit receives the signal and feeds it back to the vehicle control module; The vehicle control module takes the trajectory line planned by the lane-changing trajectory planning module as a reference, and obtains the trajectory coordinates and vehicle speed of the lane-changing through online optimization, so as to complete the tracking of the reference trajectory. 7. The guidance system according to claim 6, wherein the roadside unit adopts LTE-V/5G communication technology, including a high-gain directional beam control read-write antenna and a radio frequency controller; wherein, the high-gain directional beam The control read and write antenna is a microwave transceiver module, responsible for signal and data transmission/reception, modulation/demodulation, encoding/decoding, encryption/decryption; the radio frequency controller is a module that controls the transmission and reception of data and processes information sent and received to the upper computer ; The on-board unit is an OBU or OBD diagnostic terminal, and is a microwave device that uses the short-range communication network DSRC technology to communicate with on-board units of other vehicles; The vehicle is a vehicle with a relatively high level of L4 autonomy, and two on-board cameras are set on the vehicle, which are placed in front of the vehicle and behind the vehicle respectively. The current road environment of the vehicle is recorded by the on-board cameras, and real-time image information around the vehicle is collected; Millimeter-wave radars and lidars are installed on the vehicle; among them, 5 millimeter-wave radars are composed of a forward radar and four corner radars; 3 lidars are placed on the left, middle and right positions on the top of the vehicle; on-board cameras, The lidar signal and the millimeter-wave radar signal converted by the CAN card are jointly input into the industrial computer for perception and fusion, and the targets on the road are identified and tracked; The working condition machine is used for target-level fusion of the information data perceived by the vehicle-mounted camera, the millimeter-wave radar and the lidar, and the information after fusion is transmitted to the roadside unit through the vehicle-mounted unit. 8. The guidance system according to claim 6, wherein the road potential field model expression is as follows:

In the formula, E _S1 and E _S2 represent the potential field strength of the boundary field formed by the convoys of adjacent lanes when the right-turning vehicle changes lanes and overtaking, and the y-axis coordinate of the right-turning vehicle A at time _t is The boundary j1 and j2 axis coordinates of adjacent lanes are y _{s, j1} , y _{s, j2} ,

Represents the distance vector of vehicle A to the boundary line j1; in the same way,

represents the distance vector of the vehicle A pointing to the boundary line j2, and ρ is the road boundary field coefficient. 9. The guidance system according to claim 6, wherein the lane-changing trajectory expression is:

In the formula, x _t and y _t are the abscissa and ordinate values of the right-turning vehicle A at time t, V _t is the speed of the x-axis direction at time t, w is the lane width, and t _f is the planning time required for the vehicle to change lanes, usually t _f > 3s. 10. The guidance system according to claim 6, wherein the vehicle control module solves the trajectory coordinates and vehicle speed of the right-turning vehicle lane changing as follows: A nonlinear dynamic prediction model of vehicle motion is established, where L is the wheelbase of the own vehicle, and L _f is the distance from the center of mass to the foremost segment of the own vehicle; the state variables and control input of the own vehicle of the vehicle turning right and overtaking are X _t = [x _t , y _t , θ _t , v _t ] ^T and μ _t = [δ _t , at _t ] ^T , (x _t , y _t ) are the position coordinates of the vehicle at time t, and θ _t is the transverse direction of the vehicle at time t Swing angle, v _t is the speed of the vehicle at time t, δ _t is the steering angle of the front wheel at time t of the vehicle, and a _t is the acceleration of the vehicle at time t; Divide the Th time step into N _p steps, and use the following formula to derive the kinematic state of the vehicle at step k+1 from the state at step k:

where:

represents the abscissa of the k+1th step at time t of the vehicle when the total time step is p,

represents the ordinate of the k+1th step at time t of the vehicle when the total time step is p,

represents the yaw angle of the k+1th step at time t of the vehicle when the total time step is p,

Indicates the speed of the k+1th step of the vehicle at time t when the total time step is p;

The definition is the same as above, it is the amount of the kth step,

When the total time step is p, the acceleration of the k-th step of the vehicle at time t; Th is the elapsed time from the start of the right-turn vehicle A preparing to change lanes in the initial lane to the completion of the right-turn vehicle A's lane change.

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