TRANSIT PATH-CHOICE MODELS THAT USE REVEALED PREFERENCE AND STATED PREFERENCE DATA

Authors

S-H Lam
F Xie

Document Type

Journal Article

Publication Date

2002

Subject Area

infrastructure - vehicle, planning - surveys, land use - planning, technology - intelligent transport systems, mode - mass transit

Keywords

Travel behavior, Transit riders, Transit, Trade off analysis, Surveys, Stated preferences, Singapore, RTI, Road transport informatics, Revealed preferences, Public transit, Planning, Path choice models, Multimodal transportation, Multimodal systems, Mass transit, Local transit, IVHS, ITS (Intelligent transportation systems), Intelligent vehicle highway systems, Intelligent transportation systems, Decision making, Comparison studies, Commuters, ATT, Alternatives analysis, Advanced transport telematics

Abstract

A study was conducted of the trip-making behavior of transit users in a complex transit network with input of travel information in an increasingly complex and information-rich transit environment. A modeling framework to assess the preferences of commuters toward a range of factors and alternatives was produced. Path-choice models on transit services of Singapore were developed using mixed revealed preference (RP) and stated preference (SP) data. RP models were estimated using data obtained in the 1997 Household Interview Survey. An SP survey based on 44 scenarios was conducted, which yielded 307 responses at 12 different locations in Singapore. Models based on pure RP data, pure SP data, and mixed RP and SP data were estimated. For transit users, the decision of which path to take relies on the trade-offs among attributes of journey time and other factors. The significant attributes in the models indicate that the transit path choice is a multicriteria decision-making process. This suggests that the usual way of transit path assignment in many planning models based on single criterion, such as minimum time, may not be appropriate in choice situations. Path-choice models developed and calibrated provide important fundamental knowledge of the way transit services are to be utilized by travelers, for use in a wide range of applications, such as multimodal transit service planning models, transit demand modeling, and integration of the transit path-choice models in intelligent transportation systems applications.

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