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Influence of Public Bus Driver's Driving Behaviors on Passenger Fall Incidents: An Analysis Using Digital Tachograph Dataoa mark
  • Jeong, Harim ;
  • Park, Wonil ;
  • Lee, Jaeyoung ;
  • Park, Sungho ;
  • Yun, Ilsoo
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dc.contributor.authorJeong, Harim-
dc.contributor.authorPark, Wonil-
dc.contributor.authorLee, Jaeyoung-
dc.contributor.authorPark, Sungho-
dc.contributor.authorYun, Ilsoo-
dc.date.issued2022-01-01-
dc.identifier.urihttps://dspace.ajou.ac.kr/dev/handle/2018.oak/33182-
dc.description.abstractOwing to the low occurrence of public transport accidents, most existing studies have focused on improving the traffic safety of passenger cars. However, traffic accidents related to public transport should also be investigated for the safety of public transport users, particularly the vulnerable ones. This study analyzed the behavioral factors affecting passenger fall incidents on buses to enhance the safety of public bus passengers. This study considered potential influential factors, such as acceleration, deceleration, braking, and steering maneuvers, calculated using data from digital tachographs installed on the buses. Negative binomial and Poisson lognormal regression models were built using the Bayesian method. The two models yielded similar results. In all cases, deceleration-related behavioral factors (abrupt deceleration and abrupt stop) significantly influenced passenger fall incidents. The findings from this study are significant for establishing effective strategies to reduce fall incidents by providing safety education to bus drivers.-
dc.language.isoeng-
dc.publisherHindawi Limited-
dc.subject.meshAcceleration/deceleration-
dc.subject.meshBehavioral factors-
dc.subject.meshDigital tachographs-
dc.subject.meshDriver's driving behaviors-
dc.subject.meshInfluential factors-
dc.subject.meshNegative binomial-
dc.subject.meshPoisson lognormal regressions-
dc.subject.meshPublic bus-
dc.subject.meshPublic transport-
dc.subject.meshTraffic safety-
dc.titleInfluence of Public Bus Driver's Driving Behaviors on Passenger Fall Incidents: An Analysis Using Digital Tachograph Data-
dc.typeArticle-
dc.citation.titleJournal of Advanced Transportation-
dc.citation.volume2022-
dc.identifier.bibliographicCitationJournal of Advanced Transportation, Vol.2022-
dc.identifier.doi10.1155/2022/2941327-
dc.identifier.scopusid2-s2.0-85145878719-
dc.identifier.urlhttps://www.hindawi.com/journals/jat/-
dc.description.isoatrue-
dc.subject.subareaAutomotive Engineering-
dc.subject.subareaEconomics and Econometrics-
dc.subject.subareaMechanical Engineering-
dc.subject.subareaComputer Science Applications-
dc.subject.subareaStrategy and Management-
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Department of Transportation System Engineering
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