The Study of Light Rail Transit (LRT) Station accessibility's Mode Choice

抄録

This paper featured the station access choice study of future light rail transit (LRT) network of Nakhon Ratchasima, Thailand. A binary logit model was developed to reflect the access mode choice decision between feeder system and private cars. The questionnaires were distributed to 425 local respondents to study their preferences of transport attributes. The LRT station accessibility was evaluated using Detour Index and incorporated to utility functions in the logit model. The model performance was then tested by Machine Learning (ML) technique. The research findings revealed that traditional influential factors include travel cost, travel time, and income levels. In addition, station accessibility in form of Detour Index also show significance in access mode choice for Nakhon Ratchasima residents. Thus, the LRT development plan should utterly consider establishing accessibility improvement policy to effectively promote public transport usage.