Please use this identifier to cite or link to this item: https://doi.org/10.1155/2015/410234
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dc.titleBus Travel Time Deviation Analysis Using Automatic Vehicle Location Data and Structural Equation Modeling
dc.contributor.authorGong, X
dc.contributor.authorGuo, X
dc.contributor.authorDou, X
dc.contributor.authorLu, L
dc.date.accessioned2020-10-26T06:54:56Z
dc.date.available2020-10-26T06:54:56Z
dc.date.issued2015
dc.identifier.citationGong, X, Guo, X, Dou, X, Lu, L (2015). Bus Travel Time Deviation Analysis Using Automatic Vehicle Location Data and Structural Equation Modeling. Mathematical Problems in Engineering 2015 : 410234. ScholarBank@NUS Repository. https://doi.org/10.1155/2015/410234
dc.identifier.issn1024-123X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/180095
dc.description.abstractTo investigate the influences of causes of unreliability and bus schedule recovery phenomenon on microscopic segment-level travel time variance, this study adopts Structural Equation Modeling (SEM) to specify, estimate, and measure the theoretical proposed models. The SEM model establishes and verifies hypotheses for interrelationships among travel time deviations, departure delays, segment lengths, dwell times, and number of traffic signals and access connections. The finally accepted model demonstrates excellent fitness. Most of the hypotheses are supported by the sample dataset from bus Automatic Vehicle Location system. The SEM model confirms the bus schedule recovery phenomenon. The departure delays at bus terminals and upstream travel time deviations indeed have negative impacts on travel time fluctuation of buses en route. Meanwhile, the segment length directly and negatively impacts travel time variability and inversely positively contributes to the schedule recovery process; this exogenous variable also indirectly and positively influences travel times through the existence of signalized intersections and access connections. This study offers a rational approach to analyzing travel time deviation feature. The SEM model structure and estimation results facilitate the understanding of bus service performance characteristics and provide several implications for bus service planning, management, and operation. © 2015 Xiaolin Gong et al.
dc.publisherHindawi Publishing Corporation
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20201031
dc.subjectBus transportation
dc.subjectCrashworthiness
dc.subjectRecovery
dc.subjectTraffic control
dc.subjectTraffic signals
dc.subjectAutomatic vehicle location systems
dc.subjectAutomatic vehicle locations
dc.subjectEstimation results
dc.subjectExogenous variables
dc.subjectSchedule recovery
dc.subjectSignalized intersection
dc.subjectStructural equation modeling
dc.subjectTravel time variabilities
dc.subjectTravel time
dc.typeArticle
dc.contributor.departmentCIVIL AND ENVIRONMENTAL ENGINEERING
dc.description.doi10.1155/2015/410234
dc.description.sourcetitleMathematical Problems in Engineering
dc.description.volume2015
dc.description.page410234
dc.published.statePublished
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