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An improved cellular automaton with axis information for microscopic traffic simulation
Institution:1. Department of Bridge Engineering, Tongji University, Shanghai 200092, China;2. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China;1. School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China;2. Department of Civil Engineering, The University of Hong Kong, Hong Kong, China;3. School of Social Development and Public Policy, Fudan University, Shanghai 200433, China;4. Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China;1. Nottingham University Business School, Nottingham, UK;2. Universitat Pompeu Fabra, Barcelona, Spain;3. Physik von Transport und Verkehr, Universität Duisburg–Essen, 47048 Duisburg, Germany;4. Rhine-Waal University of Applied Sciences, 47533 Kleve, Germany;1. Universidade Federal Rural do Rio de Janeiro, Brazil;2. Federal Fluminense University, Brazil;3. LNCC and Federal University of Juiz de Fora, Brazil
Abstract:Cellular Automaton (CA), an efficient dynamic modeling method that is widely used in traffic engineering, is newly introduced for traffic load modeling. This modeling method significantly addresses the modest traffic loads for long-span bridges. It does, however, require improvement to calculate precise load effects. This paper proposed an improved cellular automaton with axis information, defined as the Multi-axle Single-cell Cellular Automaton (MSCA), for the precise micro-simulation of random traffic loads on bridges. Four main ingredients of lattice, cells’ states, neighborhoods and transition rules are redefined in MSCA to generate microscopic vehicle sequences with detailed vehicle axle positions, user-defined cell sizes and time steps. The simulation methodology of MSCA is then proposed. Finally, MSCA is carefully calibrated and validated using site-specific WIM data. The results indicate: (1) the relative errors (REs) for the traffic parameters, such as volumes, speeds, weights, and headways, from MSCA are basically no more than ±10% of those of WIM data; (2) the load effects of three typical influence lines (ILs) with varied lengths of 50, 200 and 1000 m are also confidently comparable, both of which validate the rationality and precision of MSCA. Furthermore, the accurate vehicle parameters and gaps generated from MSCA can be applied not only for precise traffic loading on infrastructures but also for the accurate estimation of vehicle dynamics and safety. Hence, wide application of MSCA can potentially be expected.
Keywords:Bridge  Traffic load  Microsimulation  Cellular automaton (CA)  Weigh-in-motion (WIM)  Multi-axle single-cell cellular automaton (MSCA)
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