Spatial interaction model for trip-chaining behavior based on entropy maximizing method

Yudai Honma, Osamu Kurita, Azuma Taguchi

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this paper, we propose a new spatial interaction model for trip-chaining behavior that consists of a sequence of movements. Particularly, including the origin-destination constraints, we generalize the traditional entropy maximizing model to deal with trip-chaining behaviors. Traditional entropy models should be noted in terms of a theoretical derivation of the gravity model and its validity to real data. However, these models only deal with simple movements from origin to destination. On the contrary, people frequently visit several destinations in one trip and make a sequence of movements. In this regard of view, we extend the traditional entropy model, and propose a general framework for deriving trip-chain distributions incorporating a sequence of movements. This model enables us to estimate the trip-chain distribution to maximize the entropy under several constraints. Finally, we apply the model to a person trip survey in the Tokyo metropolitan area to examine the validity of the model.

Original languageEnglish
Pages (from-to)235-254
Number of pages20
JournalJournal of the Operations Research Society of Japan
Volume53
Issue number4
Publication statusPublished - 2010 Dec

Fingerprint

Spatial interaction
Entropy
Destination
Metropolitan areas
Gravity model
Tokyo

Keywords

  • Entropy maximizing method
  • Multiple destinations
  • Spatial interaction model
  • Tokyo metropolitan area
  • Transportation
  • Trip-chain

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Decision Sciences(all)

Cite this

Spatial interaction model for trip-chaining behavior based on entropy maximizing method. / Honma, Yudai; Kurita, Osamu; Taguchi, Azuma.

In: Journal of the Operations Research Society of Japan, Vol. 53, No. 4, 12.2010, p. 235-254.

Research output: Contribution to journalArticle

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