Modeling Mode and Route Similarities in Network Equilibrium Problem with Go-Green Modes

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• 作者：Songyot Kitthamkesorn ; Anthony Chen ; Xiangdong Xu…
• 关键词：Nested logit ; Cross ; nested logit ; Mathematical programming formulation ; Combined modal split and traffic assignment problem
• 刊名：Networks and Spatial Economics
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：16
• 期：1
• 页码：33-60
• 全文大小：1,243 KB
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• 作者单位：Songyot Kitthamkesorn (1)
  Anthony Chen (1)
  Xiangdong Xu (2)
  Seungkyu Ryu (1)
  
  1. Department of Civil and Environmental Engineering, Utah State University, Logan, UT, 84322-4110, USA
  2. Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
  
• 刊物类别：Business and Economics
• 刊物主题：Economics
  Regional Science
  Civil Engineering
  Operation Research and Decision Theory
  
• 出版者：Springer Netherlands
• ISSN：1572-9427

文摘

Environmental sustainability is a common requirement on the development of various real-world systems, especially on road transportation systems. Motorized vehicles generate a large amount of harmful emissions, which have adverse effects to the environment and human health. Environmental sustainability requires more promotions of ‘go-green’ transportation modes such as public transit and bicycle to realize the increasing travel demands while keeping the environmental expenses low. In this paper, we make use of recent advances in discrete choice modeling to develop equivalent mathematical programming formulations for the combined modal split and traffic assignment (CMSTA) problem that explicitly considers mode and route similarities under congested networks. Specifically, a nested logit model is adopted to model the modal split problem by accounting for mode similarity among the available modes, and a cross-nested logit model is used to account for route overlapping in the traffic assignment problem. This new CMSTA model has the potential to enhance the behavioral modeling of travelers’ mode shift between private motorized mode and ‘go-green’ modes as well as their mode-specific route choices, and to assist in quantitatively evaluating the effectiveness of different ‘go-green’ promotion policies.