System performance and user response under real-time information in a congested traffic corridor |
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| Institution: | 1. School of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang 330013, China;7. Key Laboratory of Advanced Control & Optimization of Jiangxi Province, Nanchang 330013, China;1. School of Economics and Management, Beihang University, Beijing 100191, China;2. Key Lab of Complex System Analysis and Management Decision, Ministry of Education, Beijing 100191, China;3. Beijing Institute for Advanced Studies, National University of Defense Technology, Beijing 100101, China;4. College of Systems Engineering, National University of Defense Technology, Changsha, Hunan 410073, China;5. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China;6. Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China;7. Beijing International Science and Technology Cooperation Base for City Safety Operation and Emergency Support, Beijing 100191, China;1. Department of Civil and Environmental Engineering, Pennsylvania State University, University Park, PA 16802-1408, USA;2. Department of Civil and Environmental Engineering, Pennsylvania State University, 212 Sackett Building, University Park, PA 16802-1408, USA;3. School of Sustainable Engineering and the Built Environment, Arizona State University, College Avenue Commons, Room 474, 660 S. College Avenue, Tempe, AZ 85287, USA;1. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR;2. Beijing Key Laboratory of Big Data Management and Analysis Methods, Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China |
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| Abstract: | A modelling framework is developed to analyze the effect of in-vehicle real time information strategies on the performance of a congested traffic communing corridor. The framework consists of a special-purpose simulation component and a user decisions component that determines users' responses to the supplied information. The user decisions component is microscopic and determines individual commuters' route switching, at any node of the network, as a function of the supplied information. The traffic simulation component moves vehicles in bundles or macroparticles at the prevailing local speeds, as determined by macroscopic traffic relations. The framework allows the investigation of system performance under alternative behavioral response mechanisms, as well as under different information strategies. Results are presented for simulation experiments in a commuting corridor with a special network structure that simplifies the network computations. The results illustrate the effect of the fraction of users equipped with in-vehicle navigation systems on overall system performance. In addition, alternative assumptions on user response reflecting varying degrees of optimizing behavior are explored. The modelling framework is shown to provide a useful approach for addressing key questions of interest in the design of real time in-vehicle information system. |
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