Bus stop spacing with heterogeneous trip lengths and elastic demand

IF 5.8 1区 工程技术 Q1 ECONOMICS Transportation Research Part B-Methodological Pub Date : 2024-11-01 DOI:10.1016/j.trb.2024.103022
Ayush Pandey, Lewis J. Lehe
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Abstract

This paper develops models of a bus route in which (i) stop spacing can vary; (ii) trip lengths are heterogeneous; (iii) demand is elastic; and (iv) passengers delay the bus. Since wider spacings make sufficiently long trips faster, and sufficiently short trips slower, they induce long trips and repel short trips. We explore two continuum-approximation models: one with fixed headways and another in which headways depend on the spacing. The pattern of induced/repelled trips means the ridership-maximizing spacing is shorter than the one that maximizes passenger-km traveled. The same pattern also makes the average trip length endogenous to spacing. In the model with endogenous headways, when spacing is very narrow, a rise in spacing can reduce the expected wait time by more than it increases the expected walk time. We draw several lessons for practice and use a discrete simulation to confirm results from the continuous approximation models.
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具有异质行程长度和弹性需求的巴士站间距
本文建立了一个公交线路模型,在该模型中,(i) 站间距可以变化;(ii) 行程长度是异质的;(iii) 需求是有弹性的;(iv) 乘客会延迟乘坐公交车。由于较宽的站间距会使足够长的行程变得更快,而足够短的行程变得更慢,因此它们会诱发长行程而排斥短行程。我们探讨了两个连续近似模型:一个是固定班次,另一个是班次取决于间隔。诱导/排斥出行的模式意味着乘客量最大化的间距比乘客出行公里数最大化的间距要短。同样的模式也使得平均行程长度与间距相关。在具有内生班次间隔的模型中,当班次间隔非常窄时,增加班次间隔所减少的预期等待时间比增加的预期步行时间要多。我们总结了一些实践经验,并使用离散模拟来确认连续近似模型的结果。
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来源期刊
Transportation Research Part B-Methodological
Transportation Research Part B-Methodological 工程技术-工程:土木
CiteScore
12.40
自引率
8.80%
发文量
143
审稿时长
14.1 weeks
期刊介绍: Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.
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