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Empirical Analysis of Factors Influencing Potential Demand of Customized Buses in Shanghai, China
The customized bus (CB) is an emerging commute mode in China, and it is operated flexibly with schedules arranged based on online reservations. However, a CB can only be operated with sufficient travel demand. This paper aims to develop a commute mode choice model to explore influential factors on the potential demand for CBs in Shanghai, China, and specify their impacts. Revealed preference (RP) and stated preference (SP) data are collected from a questionnaire survey and integrated with skim data from road and transit network analysis. The study focuses on commuters in morning peak hours using six main modes, including CB. A SP survey collected commuters’ preference for CBs under hypothetical scenarios based on CB’s unit fare, operating speed, and travel time fluctuation levels. Variables significantly influencing mode choice are specified in the model, including level-of-service (LOS) and socioeconomic and demographic attributes. The model indicates that the CB’s fare, in-vehicle time, and travel time fluctuation negatively affect the potential demand for CBs. Part-time students, the middle-aged, or well-educated commuters are more likely to use a CB, whereas male, low-income, or poorly educated people show less tendency to shift to a CB. The developed model is expected to be applied in a citywide travel demand model and provide reference for policy-making.
Empirical Analysis of Factors Influencing Potential Demand of Customized Buses in Shanghai, China
The customized bus (CB) is an emerging commute mode in China, and it is operated flexibly with schedules arranged based on online reservations. However, a CB can only be operated with sufficient travel demand. This paper aims to develop a commute mode choice model to explore influential factors on the potential demand for CBs in Shanghai, China, and specify their impacts. Revealed preference (RP) and stated preference (SP) data are collected from a questionnaire survey and integrated with skim data from road and transit network analysis. The study focuses on commuters in morning peak hours using six main modes, including CB. A SP survey collected commuters’ preference for CBs under hypothetical scenarios based on CB’s unit fare, operating speed, and travel time fluctuation levels. Variables significantly influencing mode choice are specified in the model, including level-of-service (LOS) and socioeconomic and demographic attributes. The model indicates that the CB’s fare, in-vehicle time, and travel time fluctuation negatively affect the potential demand for CBs. Part-time students, the middle-aged, or well-educated commuters are more likely to use a CB, whereas male, low-income, or poorly educated people show less tendency to shift to a CB. The developed model is expected to be applied in a citywide travel demand model and provide reference for policy-making.
Empirical Analysis of Factors Influencing Potential Demand of Customized Buses in Shanghai, China
Li, Dongjin (Autor:in) / Ye, Xin (Autor:in) / Ma, Jie (Autor:in)
12.03.2019
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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