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- W2200046305 abstract "Abstract More than 40% of crashes that involve bicycles have occurred at intersections. According to the FARS database, an average of more than 30% of cyclist fatalities occurred at intersections from 2008 to 2012. Furthermore, up to 16% of bicycle-related crashes resulted from cyclist violations (i.e. bicyclists ride out at signalized or sign-controlled intersections). Not only has bicycle safety at intersections been a serious issue, but also the growing number of bicycle commuters makes the problem even more important. For example from 2000 to 2011, bicycle commuting rates in the US increased by 80% in large Bicycle Friendly Cities (BFCs), by 32% in non-BFCs, and overall by 47%. Moreover, improving bicycle safety should be considered more seriously to promote sustainable and eco-friendly modes of transport. For several different reasons (e.g. inattention, distraction, etc.), cyclists fail to obey traffic rules at both signalized and sign-controlled intersections. Hence the problem is how to prevent/mitigate these intersection-related crashes that involve bicycles. Failures to comply need to be identified before they occur so actions can be taken to alleviate the consequences. The focus of this paper is to present a system architecture that incorporates naturalistic cycling data to develop cyclist violation prediction models at intersections." @default.
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- W2200046305 date "2015-01-01" @default.
- W2200046305 modified "2023-09-26" @default.
- W2200046305 title "Developing a System Architecture for Cyclist Violation Prediction Models Incorporating Naturalistic Cycling Data" @default.
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- W2200046305 doi "https://doi.org/10.1016/j.promfg.2015.07.724" @default.
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