ABSTRACT

Bicycling is a popular method of transportation and recreational activity utilized ubiquitously around the world. In the United States alone thousands of active cycling clubs exist, in addition to the millions of riders who ride independently, and cycling has shown a continual steady increase for decades. As cycling becomes more and more popular, a commensurate increase in cycling accidents and fatalities has also occurred. Regardless of current safety interventions employed hundreds of cyclist fatalities and tens of thousands of cyclist injuries are recorded/reported annually. Cycling accidents are estimated to cost billions of dollars in damages, medical expenses, lost wages, and insurance. The current body of literature may not comprehensively take into account important factors associated with unsafe cycling behaviors and resulting cycling safety efforts may be predicated on this incomplete information. Thus, my doctoral research focuses on investigating cognitive drivers of unsafe cycling behaviors through multiple studies.

Study 1 was a systematic review of the current unsafe cycling behavior literature utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. Emergent themes from this review were incomplete representations of actual behaviors, shortcomings associated with the various methodological approaches employed, and scant understanding of why cyclists choose to ride unsafely. Study 2 utilized an observational approach to identify actual rates of unsafe cycling behaviors across different infrastructure design characteristics. Accident data in conjunction with laws governing cyclists drove the selection of behaviors observed (e.g., failing to stop at a stop light or making an illegal turn), and infrastructure design characteristics (e.g., enhanced pedestrian walkway or staggered t-intersection) were identified via established parameters according to the Department of Transportation. High rates of unsafe behaviors were consistently seen across locations including, for example, failing to stop at a stop light and failing to yield to traffic. Significant differences across locations were, for instance, making an illegal turn and riding in an unauthorized area. Study 3 employed questionnaires to quantitatively examine several cognitive drivers of unsafe cycling behaviors. Factors that impact cyclists’ decisions to ride unsafely, as well as unsafe behavioral outcomes, were analyzed using Analytic Hierarchy Process (AHP) and Policy Capturing methodologies. Results indicated which factors were significant (e.g., if the cyclist is running late or has ample time to reach their destination) and which were not (e.g., the presence or lack of a dedicated bicycle path) within the decision making process to ride unsafely. Finally, the overall results of the studies were synthesized into a policy statement outlining major findings and recommendations to inform future legal, civil, and academic endeavors associated with cycling safety interventions.