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Accid Anal Prev ; 122: 99-107, 2019 Jan.
Article in English | MEDLINE | ID: mdl-30340148

ABSTRACT

Red light running is one of the most common traffic violations among cyclists. From different surveys, we know that about 40% of all cyclists run a red light at least occasionally. However, specific data on red light running of e-bike riders (pedelec and S-pedelec riders), a population of cyclists that has been growing steadily in the past few years in Germany and elsewhere, is largely missing. Similarly unclear is the role of the used infrastructure (e.g., carriageway or bike path) or the intersection type on the riders' propensity to run the red light. The goal of this study was to investigate the red light running behaviour of three different bicycle types (bicycle, pedelec, S-pedelec) in Germany, with specific focus on various infrastructure characteristics. We reanalysed data obtained in a naturalistic cycling study, in which we observed 90 participants riding their own bicycles (conventional bicycles, pedelecs, S-pedelecs) on their daily trips over four weeks each. The video material of these trips was annotated and analysed with regard to red light running. Overall, our participants experienced nearly 8000 red light situations. In 16.3% of these situations, they ran the red light, with nearly identical rates for cyclists, pedelec and S-pedelec riders. Red light running rates were lowest when cyclists rode on the carriageway, while the complexity of the intersection appeared to play a role as well. In general, red light running was more common when riders were about to turn right instead of turning left or riding straight through the intersection. Interestingly, we also observed a considerable number of cases in which the riders changed their used infrastructure (e.g., from the carriageway onto the pavement) to avoid a red light.


Subject(s)
Bicycling/statistics & numerical data , Built Environment , Law Enforcement/methods , Accidents, Traffic/prevention & control , Adult , Bicycling/legislation & jurisprudence , Bicycling/psychology , Color , Female , Germany , Humans , Lighting/statistics & numerical data , Male , Risk-Taking , Video Recording , Young Adult
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