Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/97426
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorDing, Hen_US
dc.creatorSze, NNen_US
dc.creatorGuo, Yen_US
dc.creatorLi, Hen_US
dc.date.accessioned2023-03-06T01:18:23Z-
dc.date.available2023-03-06T01:18:23Z-
dc.identifier.issn0001-4575en_US
dc.identifier.urihttp://hdl.handle.net/10397/97426-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2021 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Ding, H., Sze, N. N., Guo, Y., & Li, H. (2021). Role of exposure in bicycle safety analysis: Effect of cycle path choice. Accident Analysis & Prevention, 153, 106014 is available at https://dx.doi.org/10.1016/j.aap.2021.106014.en_US
dc.subjectBicycle crash prediction modelen_US
dc.subjectBicycle distance traveleden_US
dc.subjectBicycle safetyen_US
dc.subjectExposureen_US
dc.subjectShortest path methoden_US
dc.titleRole of exposure in bicycle safety analysis : effect of cycle path choiceen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume153en_US
dc.identifier.doi10.1016/j.aap.2021.106014en_US
dcterms.abstractDespite the recognized environmental and health benefits of cycling, bicyclists are vulnerable to severe injuries and mortalities in the road crashes. Therefore, it is of paramount importance to identify the possible factors that may affect the bicycle crash risk. However, reliable estimates of bicycle exposure are often not available for the safety risk evaluation of different entities. The objective of this study is to advance the estimation of exposure in the bicycle safety analysis, using the detailed origin-destination data of each trip of the London public bicycle rental system. Two approaches including shortest path method (SPM) and weighted shortest path method (WSPM) are proposed to model the bicycle path choice and to estimate the bicycle distance traveled (BDT). Then, the bicycle crash frequency models that adopt BDTs as the exposure estimated using SPM and three WSPMs are developed. Three exposure measures including bicycle trips, bicycle time traveled (BTT), and BDT are assessed. Results indicate that the bicycle crash frequency models that incorporate the BDTs using WSPM have superior model fit. Moreover, the bicycle crash frequency model that incorporate the BDTs as the exposure outperforms those that incorporate the bicycle trips and BTT as the exposures. Findings of current study are indicative to the development of bicycle crash frequency model. Moreover, it should enhance the understanding on the roles of environmental, traffic and bicyclist factors in bicycle crash risk, based on appropriate estimates of bicycle exposures. Therefore, it should be useful to the transport planners and engineers for the development of bicycle infrastructures that can improve the overall bicycle safety in the long run.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAccident analysis and prevention, Apr. 2021, v. 153, 106014en_US
dcterms.isPartOfAccident analysis and preventionen_US
dcterms.issued2021-04-
dc.identifier.scopus2-s2.0-85100456756-
dc.identifier.pmid33578270-
dc.identifier.artn106014en_US
dc.description.validate202203 bcfcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-0388-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Polytechnic University; National Natural Science Foundation of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS44644239-
dc.description.oaCategoryGreen (AAM)en_US
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