A stochastic multimodal reliable network design problem under adverse weather conditions

Kenetsu Uchida, Agachai Sumalee, H. W. Ho

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

Abstract

This paper formulates a network design problem (NDP) for finding the optimal public transport service frequencies and link capacity expansions in a multimodal network with consideration of impacts from adverse weather conditions. The proposed NDP aims to minimize the sum of expected total travel time, operational cost of transit services, and construction cost of link capacity expansions under an acceptable level of variance of total travel time. Auto, transit, bus, and walking modes are considered in the multimodal network model for finding the equilibrium flows and travel times. In the proposed network model, demands are assumed to follow Poisson distribution, and weather-dependent link travel time functions are adopted. A probit-based stochastic user equilibrium, which is based on the perceived expected travel disutility, is used to determine the multimodal route of the travelers. This model also considers the strategic behavior of the public transport travelers in choosing their routes, that is, common-line network. Based on the stochastic multimodal model, the mean and variance of total travel time are analytical estimated for setting up the NDP. A sensitivity-based solution algorithm is proposed for solving the NDP, and two numerical examples are adopted to demonstrate the characteristics of the proposed model.
Original languageEnglish
Pages (from-to)73-95
Number of pages23
JournalJournal of Advanced Transportation
Volume49
Issue number1
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • multimodal transport network
  • network design problem
  • sensitivity analysis
  • stochastic network
  • uncertainty

ASJC Scopus subject areas

  • Automotive Engineering
  • Economics and Econometrics
  • Mechanical Engineering
  • Computer Science Applications
  • Strategy and Management

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