|Table of Contents|

Vehicle-infrastructure cooperative control method of connected and signalized intersection in mixed traffic environment(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2022年03期
Page:
139-151
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Vehicle-infrastructure cooperative control method of connected and signalized intersection in mixed traffic environment
Author(s):
WANG Run-min1; 2; 3;  ZHANG Xin-rui2;  ZHAO Xiang-mo1; 2; 3;  WU Xia1; 2; 3;  FAN Hai-jin2
(1. Collaborative Innovation Center for Western Traffic Safety and Intelligent Control by Province and Ministry, Chang'an University, Xi'an 710018, Shaanxi, China; 2. School of Information Engineering, Chang'an University, Xi'an 710064, Shaanxi, China; 3. Joint Laboratory for Internet of Vehicles of Ministry of Education-China Mobile Communications Corporation, Chang'an University, Xi'an 710018, Shaanxi, China)
Keywords:
vehicle-infrastructure cooperation;  intelligent and connected vehicle;  signalized intersection;  mixed traffic environment;  penetration rate
PACS:
U491.2
DOI:
10.19818/j.cnki.1671-1637.2022.03.011
Abstract:
In order to improve the adaption of intelligent vehicle-infrastructure cooperative control methods around connected and signalized intersection to real traffic environment, a novel intelligent vehicle-infrastructure cooperative optimization control method was proposed under the traffic scene of eight-phase connected and signalized intersection mixed intelligent and connected vehicle(ICV)with connected and human-driven vehicle(CHV). Based on modeling the kinematic characteristics and car-following behavior of ICV in the mixed traffic scene, a mixed platoon was formed. A rolling optimization-based cooperative control method of traffic signal and ICV trajectory was proposed based on the platoon model, safety constraints, and fuel consumption model. The cooperative control problem was divided into two layers based on the idea of asynchronous hierarchical optimization, the upper layer was traffic signal timing optimization, and the lower layer was ICV trajectory optimization. Taking the travel time delay and fuel consumption of the vehicle at the intersection as the optimization objectives, the genetic algorithm and three-stage trajectory optimization method were used to solve the traffic signal timing optimization and ICV trajectory optimization, respectively. The stability of the mixed vehicle platoon was verified under different steady-state speeds and penetration rates of ICV. The control effect of the proposed control method and the influence of key parameters on the control effect were analyzed. Analysis results indicate that the proposed control method can effectively improve the traffic efficiency and fuel economy of the intersection under various traffic flows and penetration rates of ICV. In the total ICV environment, the indexes respectively improve by 57.3% and 13.3% when the proposed control method is compared with the method without optimization. Compared with the condition without penetration, with the increase of the penetration rate of ICV, the control efficiency of the proposed control method constantly improves, and the indexes respectively increase by 42.0% and 14.2%. Even if the penetration rate of ICV is only 20%, the proposed control method can also achieve 20.4% improvement in the term of traffic efficiency. The longer traffic signal cycle and the shorter driver reaction time of CHV can provide a benefit for the cooperative control effect.2 tabs, 13 figs, 40 refs.

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Last Update: 2022-07-20