Bus user itinerary choice: Can crowding information help shift riders?

IF 2.4 Q3 TRANSPORTATION
Long Pan , E.O.D. Waygood , Zachary Patterson
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引用次数: 0

Abstract

This study addresses the challenges posed by the unbalanced distribution of ridership on public transit, which often leads to issues such as bus overcrowding and bunching. We investigated the influence of crowding information on public transit users’ decisions to switch to less crowded itineraries. By conducting a Discrete Choice Experiment, we gathered data from transit users to estimate a mixed logit model, analyzing how various factors impact itinerary choice behavior. The results indicate that bus crowding information, alongside context information, service details of the itinerary, and incentives significantly affect users’ choices. Specifically, crowding information has a notable statistical impact on the decision-making process, depending on the proposed itinerary mode. For example, when the proposed mode is a bus, respondents show a preference for itineraries with more available seats (odds ratio = 1.058 per seat). Conversely, in scenarios involving a shared taxi, respondents are less inclined to switch if traveling with co-riders (odds ratio = 0.693). The study also quantifies the trade-offs among crowding information, service information, and incentives. Our findings provide insights that can assist public transit operators in managing demand more effectively, potentially enhancing operational efficiency and reducing costs.
公交用户行程选择:拥挤信息能否帮助转移乘客?
这项研究解决了公共交通乘客分布不平衡所带来的挑战,这经常导致公共汽车过度拥挤和拥挤等问题。我们调查了拥挤信息对公共交通用户选择不那么拥挤路线的影响。通过离散选择实验(Discrete Choice Experiment),我们从公交用户中收集数据,估计混合logit模型,分析各种因素如何影响行程选择行为。结果表明,公交拥挤信息、环境信息、路线服务细节和激励因素对用户选择有显著影响。具体而言,拥挤信息对决策过程具有显著的统计影响,这取决于所提议的行程模式。例如,当建议的模式是公共汽车时,受访者表现出对有更多可用座位的行程的偏好(优势比= 1.058 /座位)。相反,在涉及共享出租车的场景中,如果与其他乘客一起出行,受访者不太愿意更换(优势比= 0.693)。该研究还量化了拥挤信息、服务信息和激励之间的权衡。我们的研究结果可以帮助公共交通运营商更有效地管理需求,从而有可能提高运营效率并降低成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.00
自引率
12.00%
发文量
222
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