Rhythmic Control of Automated Traffic—Part II: Grid Network Rhythm and Online Routing

Xi Lin (), Meng Li (), Zuo-Jun Max Shen (), Yafeng Yin () and Fang He ()
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Xi Lin: Department of Civil Engineering, Tsinghua University, Beijing 100084, People’s Republic of China
Meng Li: Department of Civil Engineering, Tsinghua University, Beijing 100084, People’s Republic of China
Zuo-Jun Max Shen: Department of Industrial Engineering and Operations Research, University of California Berkeley, Berkeley, California 94720; Department of Civil and Environmental Engineering, University of California Berkeley, Berkeley, California 94720
Yafeng Yin: Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, Michigan 48109; Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109
Fang He: Department of Industrial Engineering, Tsinghua University, Beijing 100084, People’s Republic of China

Transportation Science, 2021, vol. 55, issue 5, 988-1009

Abstract: Connected and automated vehicle (CAV) technology is providing urban transportation managers tremendous opportunities for better operation of urban mobility systems. However, there are significant challenges in real-time implementation as the computational time of the corresponding operations optimization model increases exponentially with increasing vehicle numbers. Following the companion paper (Chen et al. 2021), which proposes a novel automated traffic control scheme for isolated intersections, this study proposes a network-level, real-time traffic control framework for CAVs on grid networks. The proposed framework integrates a rhythmic control method with an online routing algorithm to realize collision-free control of all CAVs on a network and achieve superior performance in average vehicle delay, network traffic throughput, and computational scalability. Specifically, we construct a preset network rhythm that all CAVs can follow to move on the network and avoid collisions at all intersections. Based on the network rhythm, we then formulate online routing for the CAVs as a mixed integer linear program, which optimizes the entry times of CAVs at all entrances of the network and their time–space routings in real time. We provide a sufficient condition that the linear programming relaxation of the online routing model yields an optimal integer solution. Extensive numerical tests are conducted to show the performance of the proposed operations management framework under various scenarios. It is illustrated that the framework is capable of achieving negligible delays and increased network throughput. Furthermore, the computational time results are also promising. The CPU time for solving a collision-free control optimization problem with 2,000 vehicles is only 0.3 second on an ordinary personal computer.

Keywords: rhythmic control; connected and automated vehicles; online routing; computational scalability (search for similar items in EconPapers)
Date: 2021
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