Distributed coordinated signal timing optimization in connected transportation networks |
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| Institution: | 1. Civil and Environmental Engineering Department, Washington State University, USA;2. Civil and Environmental Engineering Department, Washington State University, PO Box 642910, Pullman, WA 99164-2910, USA;1. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China;2. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, SiPaiLou #2, Nanjing 210096, China;3. Department of Civil Engineering, Monash University, Clayton, VIC 3800, Australia;4. Institute of Transport Studies, Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;1. Engineering Department, University Roma Tre, Via della Vasca Navale 79, 00146 Roma, Italy;2. University Campus Bio-Medico of Rome, via A. del Portillo 21, 00128 Rome, Italy;1. Department of Civil and Environmental Engineering, University of Virginia, P.O. Box 400742, Charlottesville, VA 22904-4742, United States;2. Department of Transportation and Urban Infrastructure Studies, Morgan State University, 1700 E. Cold Spring Lane, Baltimore, MD 21251, United States;1. School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ 85281, USA;2. School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287, USA |
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| Abstract: | This paper presents a Distributed-Coordinated methodology for signal timing optimization in connected urban street networks. The underlying assumption is that all vehicles and intersections are connected and intersections can share information with each other. The novelty of the work arises from reformulating the signal timing optimization problem from a central architecture, where all signal timing parameters are optimized in one mathematical program, to a decentralized approach, where a mathematical program controls the timing of only a single intersection. As a result of this distribution, the complexity of the problem is significantly reduced thus, the proposed approach is real-time and scalable. Furthermore, distributed mathematical programs continuously coordinate with each other to avoid finding locally optimal solutions and to move towards global optimality. We proposed a real-time and scalable solution technique to solve the problem and applied it to several case study networks under various demand patterns. The algorithm controlled queue length and maximized intersection throughput (between 1% and 5% increase compared to the actuated coordinated signals optimized in VISTRO) and reduced travel time (between 17% and 48% decrease compared to actuated coordinated signals) in all cases. |
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| Keywords: | Distributed-coordinated approach Connected vehicles Real-time and scalable Signal timing optimization Oversaturated flow conditions |
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