Dynamic route choice behaviour and simulation-based dynamic traffic assignment model for mixed traffic flows

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Bibliografiske detaljer
Udgivet i:KSCE Journal of Civil Engineering vol. 22, no. 2 (Feb 2018), p. 813
Hovedforfatter: Ta-Yin, Hu
Andre forfattere: Chee-Chung, Tong, Tsai-Yun, Liao, Li-Wen, Chen
Udgivet:
Springer Nature B.V.
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001 2007684189
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022 |a 1226-7988 
022 |a 1976-3808 
024 7 |a 10.1007/s12205-017-1025-8  |2 doi 
035 |a 2007684189 
045 2 |b d20180201  |b d20180228 
084 |a 176037  |2 nlm 
100 1 |a Ta-Yin, Hu  |u Dept. of Transportation and Communication Management Science, National Chen Kung University, Taiwan, China 
245 1 |a Dynamic route choice behaviour and simulation-based dynamic traffic assignment model for mixed traffic flows 
260 |b Springer Nature B.V.  |c Feb 2018 
513 |a Journal Article 
520 3 |a Intelligent Transportation Systems (ITS) focus on increasing the efficiency of existing surface transportation systems through the use of advanced computers, electronics, and communication technologies. In order to perform advanced traffic management and provide travel information, dynamic traffic assignment models need to be developed to provide time-dependent estimates of traffic flows on networks in order to efficiently utilize possible advanced traffic information as well as traffic control measures. Traffic assignment distributes Origin-Destination (OD) trips in a network and determines the flow patterns in a traffic network. This research aims at developing simulation-based algorithm for dynamic traffic assignment problems under mixed traffic flow considerations. Four different physical vehicle types are explicitly considered and modeled, including car, bus, motorcycle, and truck. Four different behavioral rules, pre-specified-path driver, user-equilibrium driver, system-optimization driver, and real-time information driver, are considered in the solution procedure. The DTA algorithm consists of an inner loop that incorporates a direction finding mechanism for the search process for System Optimization (SO) and User Equilibrium (UE) classes based on the simulation results of the current iteration, including experienced vehicular trip times and marginal trip times. In order to understand tripmaker acceptance toward route guidance, a survey is conducted to explore possible behavioral classifications and associated percentages. Numerical experiments are conducted in a test network and a real city network to illustrate the capabilities of the simulation-based DTA procedures, and to observe how system performs under multiple user class’s conditions, including multiple user behavior rules and multiple physical vehicle classes. 
653 |a Economic 
653 |a Search process 
653 |a Traffic information 
653 |a Computers 
653 |a Mathematical models 
653 |a Trip estimation 
653 |a Traffic assignment 
653 |a Surveying 
653 |a Simulation 
653 |a Traffic models 
653 |a Route selection 
653 |a Direction finding 
653 |a Intelligent transportation systems 
653 |a Computer simulation 
653 |a Traffic flow 
653 |a Thermal analysis 
653 |a Traffic management 
653 |a Navigation behavior 
653 |a Iterative methods 
653 |a Procedures 
653 |a Optimization 
653 |a Traffic control 
653 |a Communication technology 
653 |a Flow pattern 
653 |a Algorithms 
700 1 |a Chee-Chung, Tong  |u Dept. of Transportation Management, Tamkang University, Tamsui, Taiwan, China 
700 1 |a Tsai-Yun, Liao  |u Dept. of Business Administration, National Chiayi University, Chiayi City, Taiwan, China 
700 1 |a Li-Wen, Chen  |u Dept. of Transportation Technology and Logistics Management, Chung Hua University, Hsinchu, Taiwan, China 
773 0 |t KSCE Journal of Civil Engineering  |g vol. 22, no. 2 (Feb 2018), p. 813 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2007684189/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/2007684189/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch