This research investigated aggressive driver–bicyclist interactions. Individuals who identified themselves as both a driver and a bicyclist were asked about their behavior when they encountered a bicyclist on the road while they were driving a car. Open-ended survey responses were analyzed from individuals who reported a propensity for driving too closely to a bicyclist who they felt was not staying to the side of the road. The data were drawn from a snowball-sampled, online survey specifically targeted to elicit responses about rare (i.e., deviant or illegal) behaviors. Little research exists on why individuals would choose to intimidate a bicyclist while they were driving. Applicable theories from sociology and behavioral economics (i.e., theories of crime as social control and as altruistic punishment) were drawn on in this study to help understand why individuals might do so. This paper argues that aggressive driving behavior directed at bicyclists in the sample population could be characterized with two general themes: “teaching them a lesson” and “they had it coming.” In both cases, individuals deflected the blame for their aggressive behavior away from themselves. Instead, they cast themselves as serving a social good by teaching bicyclists how they should behave or by punishing bicyclists for behaving in ways with which the drivers disagreed. The study reported here was an initial step in an effort to identify testable hypotheses through qualitative methods to explain such behaviors and eventually to mitigate them. The intent is to inform actionable directions to address dangerous on-street interactions that act as barriers to a safe transportation system that accommodates all users.


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    Title :

    Bicycle Backlash: Qualitative Examination of Aggressive Driver–Bicyclist Interactions


    Additional title:

    Transportation Research Record


    Contributors:


    Publication date :

    2017-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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