CN-117275261-B - Signal control and CAV track planning method based on pre-signal lamp

CN117275261BCN 117275261 BCN117275261 BCN 117275261BCN-117275261-B

Abstract

The invention discloses a signal control and CAV track planning method based on a pre-signal lamp, which comprises the steps of acquiring intersection phase information and first information according to the pre-signal lamp arranged in a cable-signal zone, acquiring second information in a regulation zone and a special lane zone, performing first model processing on the first information and the second information, predicting to obtain a vehicle motion track, acquiring the total number of vehicles and vehicle types in the regulation zone, performing second model and third model processing on the intersection phase information, the vehicle motion track, the total number of vehicles and the vehicle types, and predicting to obtain an optimal phase duration and an optimal CAV track. The invention obviously improves the traffic capacity of the intersection, obviously reduces the average oil consumption and the variable pass number of CAV, and obviously improves the traffic speed and delay of heterogeneous traffic flow.

Inventors

YU HAIYANG
WANG JIXIANG
REN YILONG
DONG CHENGLIN
CHEN SIQI

Assignees

北京航空航天大学

Dates

Publication Date: 20260512
Application Date: 20230928

Claims (7)

1. A signal control and CAV trajectory planning method based on pre-signaling lamps, comprising: Acquiring intersection phase information and first information according to a pre-signal lamp arranged in an information searching area, wherein the first information comprises HV car lamp semantic information and CAV steering demand information; acquiring second information in the regulation and control area and the special lane area, wherein the second information comprises the position, the speed, the acceleration and the lane selection information of all vehicles; the first information and the second information are subjected to first model processing, a vehicle motion track is predicted, and the total number of vehicles and the types of the vehicles in the regulation area are obtained; The method comprises the steps of carrying out second model and third model processing on intersection phase information, vehicle motion tracks, total number of vehicles and vehicle types, predicting to obtain optimal phase duration and optimal CAV track, optimizing the phase duration through the second model according to the intersection phase information, the total number of vehicles and the vehicle types, optimizing lane change strategies and vehicle acceleration by taking minimized CAV traffic delay time, CAV oil consumption and lane change cost as targets through the third model according to the vehicle motion tracks and the optimized phase duration, and determining CAV position information at the next moment according to the optimized lane change strategies and the vehicle acceleration, wherein the third model sends the CAV position information to the second model for next optimization; the expression taking the minimized CAV traffic delay time, CAV oil consumption and lane change cost as the objective functions is as follows: Wherein, the An identification number representing the CAV, Indicating the moment when CAV begins to receive trajectory optimization in the regulatory region, Is the optimal duration of CAV within the regulatory region, Is the optimal duration of CAV in the lane region of the exclusive use, An identification number indicating whether to drive into the conflict area, drive into 0, otherwise 1, A longitudinal acceleration optimization curve is represented, The number of times of channel changing is indicated, The track-changing strategy is indicated and the track-changing strategy is indicated, A weight coefficient representing the CAV traffic delay period, A weight coefficient representing CAV fuel consumption, The weight coefficient representing the cost of the lane change, The method comprises the steps of representing a time interval, restraining the objective function, wherein the restraining comprises restraining the lane changing action sequence according to a first constraint condition, and the first constraint condition comprises that the duration of a CAV continuous lane changing interval is longer than a preset minimum time interval and at most one lane can be changed every time the CAV continuously changes lanes; Constraining the movement of the vehicle according to a second constraint condition, wherein the second constraint condition comprises that the acceleration of the vehicle is between a preset maximum acceleration and a preset maximum deceleration, and the speed of the vehicle is between 0 and a preset vehicle speed limit; The longitudinal safety distance is restrained according to a third constraint condition, wherein the third constraint condition comprises that the current vehicle is kept within the longitudinal safety distance with the front vehicle and the rear vehicle respectively, and the longitudinal safety distance is determined by the speed of the current vehicle; Solving the objective function by using an improved cuckoo algorithm based on an extremum optimization algorithm, comprising: Forming a bird nest by randomly generating CAV space positions of each period, wherein the space positions comprise lane selection information and vehicle acceleration; Judging whether the preset searching times are reached, and if the preset searching times are not reached, generating a next space position for each bird nest according to the Laiweider flight; based on the space position of the next step, optimizing each bird nest through an extremum optimizing algorithm, and updating the space position of the bird nest; judging whether the maximum iteration number is reached, and if so, obtaining the optimal space position.
2. The method for signal control and CAV trajectory planning based on pre-signaling as claimed in claim 1, wherein said acquiring intersection phase information and first information according to pre-signaling signals provided in a cable domain comprises: acquiring intersection phase information according to a pre-signal lamp arranged in a cable message area, wherein the intersection phase information comprises a phase sequence and a phase duration; and according to the intersection phase information, acquiring HV car lamp semantic information and CAV steering demand information in the letter information area through a lamp language detection device.
3. The signal control and CAV trajectory planning method based on pre-signaling light as recited in claim 1, wherein the first model comprises a second-order car following model, wherein the second-order car following model processing is performed on the first information and the second information, and the specific process comprises: Acquiring current state information of a vehicle and corresponding current state information of a front vehicle according to the first information and the second information; According to the current state information of the vehicle and the corresponding current state information of the front vehicle, calculating the relative position and the relative speed between the current vehicle and the front vehicle; predicting state information of the next moment of the vehicle according to the relative position and the relative speed; And repeatedly executing the steps to determine the track of the vehicle in the process of following the front vehicle.
4. A pre-signal lamp based signal control and CAV trajectory planning method as claimed in claim 3, wherein said first model further comprises an improved lane change model, said first information and said second information being processed by a lane change model, comprising: determining that the vehicle needs to change lanes according to the first information and the second information; calculating a guiding angle according to the current position of the vehicle and the target position of the lane change; Based on the guidance angle and the current state information of the vehicle, a path planning algorithm is used to determine the trajectory of the vehicle during lane changes.
5. The method of pre-signal based signal control and CAV trajectory planning as claimed in claim 1, wherein optimizing the phase duration by the second model based on intersection phase information, total number of vehicles, and vehicle type comprises: calculating to obtain cycle duration by using a Webster optimal cycle algorithm according to intersection phase information, the total number of vehicles and the types of vehicles; And optimizing the effective green light time of each phase by using the traffic flow ratio according to the period duration, wherein the effective green light time is between the shortest effective green light time and the longest effective green light time.
6. The pre-signal based signal control and CAV trajectory planning method as recited in claim 5, wherein the second model is expressed as: Wherein, the For the optimal signal period, L is the total loss time of the intersection, Y is the sum of the traffic flow ratios of the intersection, For the effective green time of lane e, As the number of phases of the signal, As a time to loss of the signal, For lane e The red light time of the phase is set to be equal, The traffic flow ratio of the critical lane for the i-th phase, , For the effective green time of the i-th phase of lane e, Representing the shortest effective green light time of the phase; Is the longest effective green light duration of the phase.
7. A computer readable storage medium having stored thereon a computer program having stored thereon a pre-signal based signal control and CAV trajectory planning program which, when executed by a processor, implements the pre-signal based signal control and CAV trajectory planning program of any one of claims 1-6.

Description

Signal control and CAV track planning method based on pre-signal lamp Technical Field The invention relates to the technical field of intelligent transportation. And more particularly, to a signal control and CAV trajectory planning method based on pre-signaling lamps. Background The pollution emission problem at the urban intersections is serious, and the pollution emission problem is mainly caused by the great improvement of fuel consumption caused by frequent acceleration and deceleration and long-time idling of vehicles, so that the traffic management has a certain effect. From the standpoint of signal control, vehicle delays and thus consumption can be reduced by optimizing the phase sequence and green time. Accordingly, in the prior art, according to the deduced average traffic jam degree, the optimal value of the traffic light time under different traffic conditions is found. From a vehicle control perspective, ecological driving strategies may be effective in reducing fuel consumption and the strategy may be effective in reducing pollution caused by driver operation. Therefore, the prior art establishes a driver acceptance model for ecological driving strategies and indicates the significance of ecological driving for energy conservation. However, due to the rapid increase in traffic demand, conventional traffic management measures have limited effectiveness. Along with the rapid development of communication technology, a new solution idea for reducing pollution emission and travel delay is provided, and a new scheme is provided for signal control and track optimization. However, the prior art research is mostly based on the pure CAV environment or the condition of networked Human-DRIVEN VEHICLE (CHV), but in the foreseeable future, the Human driving behavior is still an irreplaceable loop in traffic, and CHV is difficult to popularize in a short period of time. Therefore, CAV is highly desirable to study in combination with Human-driven vehicles (Human-DRIVEN VEHICLE, HV). In the heterogeneous traffic flow of CAV and HV, the random factors caused by human drivers are accumulated continuously to promote the chaotic degree of the whole traffic system, so that the CAV is likely to not realize a control target due to the interference of the HV, and the optimal timing is likely to not be reached, and the most serious is the safety risk problem caused by the HV. To address this problem, the prior art proposes CAV lanes to reduce the effect of HV on the controlled system. However, most of the prior art has the default HV participating in internet connection, on the other hand, the default HV does not have lane change, which is not realistic, on the other hand, the prior art has poor traffic capacity, long delay time and no pollutant emission consideration, so that a signal control and CAV track planning method for improving traffic system traffic efficiency and reducing vehicle pollutant emission under heterogeneous traffic flow scene is needed. Disclosure of Invention The invention is based on the above-mentioned needs of the prior art, and the technical problem to be solved by the invention is to provide a signal control and CAV track planning method based on a pre-signal lamp so as to improve the communication capacity of intersections and reduce vehicle delay, CAV oil consumption and lane change times. In order to solve the problems, the invention is realized by adopting the following technical scheme: The signal control and CAV track planning method based on the pre-signal lamp comprises the steps of obtaining intersection phase information and first information according to the pre-signal lamp arranged in a traffic signal zone, wherein the first information comprises HV lamp semantic information and CAV steering requirement information, obtaining second information in a regulation zone and a special lane zone, the second information comprises positions, speeds, accelerations and lane selection information of all vehicles, carrying out first model processing on the first information and the second information, predicting to obtain a vehicle motion track, obtaining the total number of vehicles and vehicle types in the regulation zone, wherein the vehicle motion track comprises tracks of vehicles in a driving process of the vehicles following the preceding vehicle and tracks of the vehicles in a lane changing process, carrying out second model and third model processing on the intersection phase information, the vehicle motion track, the total number of the vehicles and the vehicle types, predicting to obtain optimal phase duration and optimal CAV tracks, optimizing the phase duration through the second model according to the intersection phase information, the total number of the vehicles and the vehicle types, optimizing the phase duration through the third model, optimizing the vehicle motion track and the optimal phase duration through the third model, optimizing the vehicle motion track and the ve