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July 1, 2022

Built Environment Effects on Cyclist Injury Severity in Automobile-Involved Bicycle Crashes

Chen, Peng; Shen, Qing. (2016). Built Environment Effects on Cyclist Injury Severity in Automobile-Involved Bicycle Crashes. Accident Analysis & Prevention, 86, 239 – 246.

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Abstract

This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing. (C) 2015 Elsevier Ltd. All rights reserved.

Keywords

Cycling Injuries; Traffic Accidents; Transportation Planning; Data Analysis; Employment; Built Environment; Cyclist Injury Severity; Generalized Additive Model; Generalized Ordered Logit Model; Ordered Response Model; United-states; Helmet; Frameworks; Driver; Risk