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

Songyot Kitthamkesorn, Anthony Chen, Xiangdong Xu, Seungkyu Ryu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

31 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)33-60
Number of pages28
JournalNetworks and Spatial Economics
Volume16
Issue number1
DOIs
Publication statusPublished - 1 Mar 2016
Externally publishedYes

Keywords

  • Combined modal split and traffic assignment problem
  • Cross-nested logit
  • Mathematical programming formulation
  • Nested logit

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

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