Analysis of the acceptance of park-and-ride by users: A cumulative logistic regression approach

Kai Huang

1 Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China 2 Department of Civil Engineering, Monash University, Clayton, Melbourne, Australia

Zhiyuan Liu

1 Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China

Ting Zhu

1 Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing, China

Inhi Kim

2 Department of Civil Engineering, Monash University, Clayton, Melbourne, Australia

Kun An

2 Department of Civil Engineering, Monash University, Clayton, Melbourne, Australia

DOI: https://doi.org/10.5198/jtlu.2019.1390

Keywords: Park and Ride, Traveler behaviour, Stated Preference Survey, 5-Likert Scale, Cumulative Logistic Regression


Abstract

Park-and-ride (P&R) schemes are an important way of increasing the public transport mode share, which relieves the negative impact caused by excessive automobile usage. Several existing studies have been conducted in the past to explore the factors that can influence the acceptance of P&R by travelers. However, quantitative analyses of the pertinent factors and rates of traveler choice are quite rare. In this paper, the data collected from a survey in Melbourne, Australia, is used to analyze the acceptance of P&R by travelers going to the central business district (CBD). In particular, we explore the influence that specific factors have on the choice of travel by those who are currently using P&R. The results indicate that the parking fee in the CBD area, travel time on public transport, and P&R transfer time affect traveler use of P&R. A quantitative assessment of the impact of these three factors is conducted by using a cumulative logistic regression model. Results reveal that the P&R transfer time has the highest sensitivity while public transport travel time has the least. To maximize the use of P&R facilities and public transport, insights into setting parking fees and designing P&R stations are presented.

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