Tsinghua Science and Technology  2019, Vol. 24 Issue (2): 160-170    doi: 10.26599/TST.2018.9010073
A Simulation System and Speed Guidance Algorithms for Intersection Traffic Control Using Connected Vehicle Technology
Shuai Liu, Weitong Zhang, Xiaojun Wu, Shuo Feng, Xin Pei*, Danya Yao
∙ Shuai Liu, Weitong Zhang, Shuo Feng, Xin Pei, and Danya Yao are with Department of Automation, Tsinghua University National Laboratory for Information Science and Technology (TNList), Tsinghua University, Beijing 100084, China. E-mail: liushuaicc11326@126.com; zwt15@ mails.tsinghua.edu.cn; fengshuo10@163.com; yaody@tsinghua.edu.cn.
∙ Xiaojun Wu is with Graduate School of Tsinghua University, Beijing 100084, China. E-mail: wuxiaojun@tsinghua.edu.cn.

Abstract

In the connected vehicle environment, real-time vehicle-state data can be obtained through vehicle-to-infrastructure communication, and the prediction accuracy of urban traffic conditions can significantly increase. This study uses the C++/Qt programming language and framework to build a simulation platform. A two-way six-lane intersection is set up on the simulation platform. In addition, two speed guidance algorithms based on optimizing the travel time of a single vehicle or multiple vehicles are proposed. The goal of optimization is to minimize the travel time, with common indicators such as average delay of vehicles, average number of stops, and average stop time chosen as indexes of traffic efficiency. When the traffic flow is not saturated, compared with the case of no speed guidance, single-vehicle speed guidance can improve the traffic efficiency by 20%, whereas multi-vehicle speed guidance can improve the traffic efficiency by 50%. When the traffic flow is saturated, the speed guidance algorithms show outstanding performance. The effect of speed guidance gradually enhances with increasing penetration rate, and the most obvious gains are obtained when the penetration rate increases from 10% to 40%. Thus, this study has shown that speed guidance in the connected vehicle environment can significantly improve the traffic efficiency of intersections, and the multi-vehicle speed guidance strategy is more effective than the single-vehicle speed guidance strategy.

Received: 17 May 2017      Published: 29 April 2019
Corresponding Authors: Xin Pei