Perception of Mode-Specific Travel Time Reliability and Crowding in Multimodal Trips. Issue 1 (2016)

• Record Type: Journal Article
• Authors: Li, Hao; Gao, Kun; Tu, Huizhao; Ding, Yueming; Sun, Lijun
• Is Part Of: Transportation research record. Volume 2566:Issue 1(2016)
• Page Start: 22
• Page End: 30
• Publication Date: 2016
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2566-03
• Languages: English
• ISSNs: 0361-1981

Abstract

The underutilization of public transit in Shanghai, China, calls for studies to better understand travelers' mode choice behavior in multimodal networks. This paper presents a comprehensive study of mode choice behavior and differences in the perception of travel time reliability (TTR) and crowding for different modes, particularly in multimodal networks. A two-stage stated preference survey was carried out to consider four commonly used modes, including combined-mode travel with park-and-ride, in conjunction with four key factors. The aim of the first stage was to obtain and quantify travelers' perceived TTR in relation to different levels of delay for different modes. In the second stage, an experimental design that used the utility balance theory was performed for a stated preference survey to investigate mode choice behavior and differences in perception of TTR and crowding. Results from the first stage survey showed that travelers do have different levels of tolerance regarding the longest accepted delay for different modes. Their perceived TTR in terms of a certain delay differed by mode. The results from the second stage survey provided further evidence of significant perceived differences in TTR and crowding for different modes. Mode-specific perceptions of TTR and crowding have a great impact on travelers' mode choice behavior and should be considered when forecasting models related to mode share in a multimodal network are being developed. The values of travel time, TTR, and crowding derived from this study could be used in demand forecasting and project appraisals in multimodal networks.