Determinants of pedestrian and bicyclist crash severity by party at fault in San Francisco, CA. (January 2018)
- Record Type:
- Journal Article
- Title:
- Determinants of pedestrian and bicyclist crash severity by party at fault in San Francisco, CA. (January 2018)
- Main Title:
- Determinants of pedestrian and bicyclist crash severity by party at fault in San Francisco, CA
- Authors:
- Salon, Deborah
McIntyre, Andrew - Abstract:
- Highlights: Analyses illuminate determinants of severity for pedestrian and bicyclist crashes. Many factors have the same directional effect for both pedestrians and bicyclists. Separate analyses are conducted based on party at fault. In pedestrian crashes, severity is higher when the pedestrian is at fault. For pedestrian crash analysis, accounting for party at fault is critical. Abstract: Pedestrian and bicyclist safety is of growing concern, especially given the increasing numbers of urban residents choosing to walk and bike. Sharing the roads with automobiles, these road users are particularly vulnerable. An intuitive conceptual model is proposed of the determinants of injury severity in crashes between vehicles and nonmotorized road users. Using 10 years of crash data from San Francisco, CA, we estimate logistic regression models to illuminate key determinants of crash severity for both pedestrian and bicyclist collisions. The analyses are separated by party at fault to test the novel hypothesis that environmental factors affecting driver speed and reaction time may be especially important when the driver is not at fault. Pedestrian results are broadly consistent with prior research, and offer considerable support for this hypothesis. The strongest predictors of injury severity include pedestrian advanced age, driver sobriety, vehicle type, and a set of variables that help determine driver speed and reaction time. Bicyclist results were weaker overall, and theHighlights: Analyses illuminate determinants of severity for pedestrian and bicyclist crashes. Many factors have the same directional effect for both pedestrians and bicyclists. Separate analyses are conducted based on party at fault. In pedestrian crashes, severity is higher when the pedestrian is at fault. For pedestrian crash analysis, accounting for party at fault is critical. Abstract: Pedestrian and bicyclist safety is of growing concern, especially given the increasing numbers of urban residents choosing to walk and bike. Sharing the roads with automobiles, these road users are particularly vulnerable. An intuitive conceptual model is proposed of the determinants of injury severity in crashes between vehicles and nonmotorized road users. Using 10 years of crash data from San Francisco, CA, we estimate logistic regression models to illuminate key determinants of crash severity for both pedestrian and bicyclist collisions. The analyses are separated by party at fault to test the novel hypothesis that environmental factors affecting driver speed and reaction time may be especially important when the driver is not at fault. Pedestrian results are broadly consistent with prior research, and offer considerable support for this hypothesis. The strongest predictors of injury severity include pedestrian advanced age, driver sobriety, vehicle type, and a set of variables that help determine driver speed and reaction time. Bicyclist results were weaker overall, and the distinction by party at fault was less important. … (more)
- Is Part Of:
- Accident analysis and prevention. Volume 110(2018)
- Journal:
- Accident analysis and prevention
- Issue:
- Volume 110(2018)
- Issue Display:
- Volume 110, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 110
- Issue:
- 2018
- Issue Sort Value:
- 2018-0110-2018-0000
- Page Start:
- 149
- Page End:
- 160
- Publication Date:
- 2018-01
- Subjects:
- Logit model -- Walk -- Bike -- Injury severity -- Collision
Accidents -- Prevention -- Periodicals
Accident Prevention -- Periodicals
Accidents -- Prévention -- Périodiques
363.106 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00014575 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aap.2017.11.007 ↗
- Languages:
- English
- ISSNs:
- 0001-4575
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0573.130000
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British Library HMNTS - ELD Digital store - Ingest File:
- 7004.xml