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A simulation-based dynamic traffic assignment model with combined modes

A simulation-based dynamic traffic assignment model with combined modes

Meng, Meng ORCID: 0000-0001-7240-6454, Shao, Chunfu, Zeng, Jingjing and Dong, Chunjiao (2014) A simulation-based dynamic traffic assignment model with combined modes. PROMET - Traffic & Transportation, 26 (1). pp. 65-73. ISSN 0353-5320 (Print), 1848-4069 (Online)

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This paper presents a dynamic traffic assignment (DTA) model for urban multi-modal transportation network by con­structing a mesoscopic simulation model. Several traffic means such as private car, subway, bus and bicycle are con­sidered in the network. The mesoscopic simulator consists of a mesoscopic supply simulator based on MesoTS model and a time-dependent demand simulator. The mode choice is si­multaneously considered with the route choice based on the improved C-Logit model. The traffic assignment procedure is implemented by a time-dependent shortest path (TDSP) al­gorithm in which travellers choose their modes and routes based on a range of choice criteria. The model is particularly suited for appraising a variety of transportation management measures, especially for the application of Intelligent Trans­port Systems (ITS). Five example cases including OD demand level, bus frequency, parking fee, information supply and car ownership rate are designed to test the proposed simulation model through a medium-scale case study in Beijing Chaoy­ang District in China. Computational results illustrate excel­lent performance and the application of the model to analy­sis of urban multi-modal transportation networks.

Item Type: Article
Uncontrolled Keywords: dynamic traffic assignment; combined modes; mesoscopic simulation; time-dependent shortest path algorithm
Subjects: H Social Sciences > HE Transportation and Communications
Faculty / School / Research Centre / Research Group: Faculty of Business
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group
Faculty of Business > Department of Systems Management & Strategy
Last Modified: 11 Feb 2019 16:07

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