Dynamic route choice behaviour and simulation-based dynamic traffic assignment model for mixed traffic flows
Tallennettuna:
| Julkaisussa: | KSCE Journal of Civil Engineering vol. 22, no. 2 (Feb 2018), p. 813 |
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| Päätekijä: | |
| Muut tekijät: | , , |
| Julkaistu: |
Springer Nature B.V.
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| Aiheet: | |
| Linkit: | Citation/Abstract Full Text - PDF |
| Tagit: |
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MARC
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| 001 | 2919691788 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1226-7988 | ||
| 022 | |a 1976-3808 | ||
| 024 | 7 | |a 10.1007/s12205-017-1025-8 |2 doi | |
| 035 | |a 2919691788 | ||
| 045 | 2 | |b d20180201 |b d20180228 | |
| 084 | |a 176037 |2 nlm | ||
| 100 | 1 | |a Hu, Ta-Yin |u National Chen Kung University, Dept. of Transportation and Communication Management Science, 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 Flow distribution | ||
| 653 | |a Search process | ||
| 653 | |a Traffic assignment | ||
| 653 | |a Time dependence | ||
| 653 | |a Traffic information | ||
| 653 | |a Algorithms | ||
| 653 | |a Communication technology | ||
| 653 | |a Transportation models | ||
| 653 | |a Differential thermal analysis | ||
| 653 | |a Transportation networks | ||
| 653 | |a Simulation | ||
| 653 | |a Traffic models | ||
| 653 | |a Route selection | ||
| 653 | |a Direction finding | ||
| 653 | |a Intelligent transportation systems | ||
| 653 | |a Traffic flow | ||
| 653 | |a Flow pattern | ||
| 653 | |a Traffic control | ||
| 653 | |a Traffic management | ||
| 653 | |a Iterative methods | ||
| 653 | |a Optimization | ||
| 653 | |a Computers | ||
| 653 | |a Motorcycles | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Tong, Chee-Chung |u Tamkang University, Dept. of Transportation Management, Tamsui, Taiwan, China | |
| 700 | 1 | |a Liao, Tsai-Yun |u National Chiayi University, Dept. of Business Administration, Chiayi City, Taiwan, China (GRID:grid.412046.5) (ISNI:0000 0001 0305 650X) | |
| 700 | 1 | |a Chen, Li-Wen |u Chung Hua University, Dept. of Transportation Technology and Logistics Management, Hsinchu, Taiwan, China (GRID:grid.411655.2) (ISNI:0000 0004 0638 6362) | |
| 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/2919691788/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2919691788/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |