Li, Pengfei (Tsinghua University), Chen, Yihe (Tsinghua University), Shi, Jia (Tsinghua University), Yang, Haoyu (Tsinghua University), Li, Keqiang (Tsinghua University), Luo, Yugong (Tsinghua University,Beijing)

Cooperative Schedule Optimization with Rolling Traversal Method for Connected and Automated Vehicles in a Highway Interchange

Scheduled for presentation during the Regular Session "Multi-autonomous Vehicle Studies, Models, Techniques and Simulations I" (ThBT10), Thursday, September 26, 2024, 14:50−15:10, Salon 18

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

Over the past few decades, lots of highway in- terchanges have been constructed with the development of transportation. However, both off-ramp diverging and on-ramp merging in an interchange are typical bottlenecks in highways, and growing commuting demand frequently leads to traffic breakdown in the rush hour. With advanced communication technology, connected and automated vehicles (CAVs) and cloud control system (CCS) emerge to serve as a promising solution. Among existing research, there is relatively little research on the traffic congestion issue in highway interchanges, and most of them try to address the problem from a macro perspective in traffic flow. In the field of CAVs, there are many studies addressing congestion issue within a single bottleneck. However, they can only solve local traffic congestion and might lead to downstream congestion instead. In this study, passing sequences of vehicles in the diverging area and the merging area are comprehensively considered in a mixed-integer nonlinear pro- gramming (MINLP) problem. A rolling traversal (RT) method was proposed to decompose the MINLP problem into several small-scale solvable mixed-integer linear programming (MILP) problems. We build a simulation platform in python, in which simulations at different traffic flow rate are conducted. Results suggest that compared to individually optimize the off-ramp diverging and on-ramp merging, the proposed RT method successfully reduces the overall travel delay while guaranteeing safety, especially at high traffic flow rate.