Analysis of Bicycle-Motor Vehicle Crashes in San Antonio, Texas

dc.contributor.authorBillah, Khondoker
dc.contributor.authorSharif, Hatim O.
dc.contributor.authorDessouky, Samer
dc.date.accessioned2021-09-09T13:39:23Z
dc.date.available2021-09-09T13:39:23Z
dc.date.issued2021-09-01
dc.date.updated2021-09-09T13:39:23Z
dc.description.abstractBicycling is inexpensive, environmentally friendly, and healthful; however, bicyclist safety is a rising concern. This study investigates bicycle crash-related key variables that might substantially differ in terms of the party at fault and bicycle facility presence. Employing 5 year (2014–2018) data from the Texas Crash Record and Information System database, the effect of these variables on bicyclist injury severity was assessed for San Antonio, Texas, using bivariate analysis and binary logistic regression. Severe injury risk based on the party at fault and bicycle facility presence varied significantly for different crash-related variables. The strongest predictors of severe bicycle injury include bicyclist age and ethnicity, lighting condition, road class, time of occurrence, and period of week. Driver inattention and disregard of stop sign/light were the primary contributing factors to bicycle-vehicle crashes. Crash density heatmap and hotspot analyses were used to identify high-risk locations. The downtown area experienced the highest crash density, while severity hotspots were located at intersections outside of the downtown area. This study recommends the introduction of more dedicated/protected bicycle lanes, separation of bicycle lanes from the roadway, mandatory helmet use ordinance, reduction in speed limit, prioritization of resources at high-risk locations, and implementation of bike-activated signal detection at signalized intersections.
dc.description.departmentCivil and Environmental Engineering, and Construction Management
dc.identifierdoi: 10.3390/ijerph18179220
dc.identifier.citationInternational Journal of Environmental Research and Public Health 18 (17): 9220 (2021)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/678
dc.rightsAttribution 4.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectbicycle
dc.subjectmotor vehicle
dc.subjectbicycle facility
dc.subjectlogistic regression
dc.subjectbivariate analysis
dc.titleAnalysis of Bicycle-Motor Vehicle Crashes in San Antonio, Texas
dc.typeArticle

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