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Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,

especially given the increasing numbers of residents choosing to bike and walk. Sharing

the roads with automobiles, these alternative road users are particularly vulnerable to

sustain serious injuries. With this in mind, it is important to identify the factors that

influence the

Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,

especially given the increasing numbers of residents choosing to bike and walk. Sharing

the roads with automobiles, these alternative road users are particularly vulnerable to

sustain serious injuries. With this in mind, it is important to identify the factors that

influence the severity of bicyclist and pedestrian injuries in automobile collisions. This

study uses traffic collision data gathered from California Highway Patrol’s Statewide

Integrated Traffic Records System (SWITRS) to predict the most important

determinants of injury severity, given that a collision has occurred. Multivariate binomial

logistic regression models were created for both pedestrian and bicyclist collisions, with

bicyclist/pedestrian/driver characteristics and built environment characteristics used as

the independent variables. Results suggest that bicycle infrastructure is not an important

predictor of bicyclist injury severity, but instead bicyclist age, race, sobriety, and speed

played significant roles. Pedestrian injuries were influenced by pedestrian and driver age

and sobriety, crosswalk use, speed limit, and the type of vehicle at fault in the collision.

Understanding these key determinants that lead to severe and fatal injuries can help

local communities implement appropriate safety measures for their most susceptible

road users.
ContributorsMcIntyre, Andrew (Author) / Salon, Deborah (Thesis advisor) / Kuby, Mike (Committee member) / Chester, Mikhail (Committee member) / Arizona State University (Publisher)
Created2016