dc.creatorSun, Lijun
dc.creatorTirachini Hernández, Alejandro
dc.creatorAxhausen, Kay W.
dc.creatorErath, Alexander
dc.creatorDer Horng, Lee
dc.date.accessioned2014-12-15T15:35:26Z
dc.date.available2014-12-15T15:35:26Z
dc.date.created2014-12-15T15:35:26Z
dc.date.issued2014
dc.identifierTransportation Research Part A 69 (2014) 447–460
dc.identifierdx.doi.org/10.1016/j.tra.2014.09.007
dc.identifierhttps://repositorio.uchile.cl/handle/2250/126576
dc.description.abstractUnderstanding the dynamics of boarding/alighting activities and its impact on bus dwell times is crucial to improving bus service levels. However, research is limited as conventional data collection methods are both time and labour intensive. In this paper, we present the first use of smart card data to study passenger boarding/alighting behaviour and its impact on bus dwell time. Given the nature of these data, we focus on passenger activity time and do not account for the time necessary to open and close doors. We study single decker, double decker and articulated buses and identify the specific effects of floor/ entrance type, number of activities and occupancy on both boarding and alighting dynamics. A linear relationship between average boarding and alighting times and their respective standard deviations is also found, whereas the variability of boarding and alighting time decreases with the number of passengers boarding and alighting. After observing the cumulative boarding/alighting processes under different occupancy conditions, we propose a new model to estimate passenger activity time, by introducing critical occupancy – a parameter incorporating the friction between boarding/alighting and on-board passengers. We conduct regression analyses with the proposed and another popular model for simultaneous boarding/alighting processes, finding that the critical occupancy plays a significant role in determining the regime of boarding and alighting processes and the overall activity time. Our results provide potential implications for practice and policy, such as identifying optimal vehicle type for a particular route and modelling transit service reliability.
dc.languageen
dc.publisherElsevier
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.subjectBoarding/alighting dynamics
dc.titleModels of bus boarding and alighting dynamics
dc.typeArtículo de revista


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