Description

In California, bike fatalities increased by 8.1% from 2015 to 2016. Even though the benefits of wearing helmets in protecting cyclists against trauma in cycling crash has been determined, the use of helmets is still limited, and there is opposition against mandatory helmet use, particularly for adults. Therefore, exploring perceptions of adult cyclists regarding mandatory helmet use is a key element in understanding cyclists’ behavior, and determining the impact of mandatory helmet use on their cycling rate. The goal of this research is to identify sociodemographic characteristics and cycling behaviors that are associated with the use and non-use of bicycle helmets among adults, and to assess if the enforcement of a bicycle helmet law will result in a change in cycling rates. This research develops hybrid machine learning models to pinpoint the driving factors that explain adult cyclists’ behavior regarding helmet use laws.

Publication Date

10-2021

Publication Type

Report

Topic

Bicycle and Pedestrian Issues

Digital Object Identifier

10.31979/mti.2021.2024

MTI Project

2024

Keywords

Cyclists’ behavior, machine learning classifiers, statistical analysis

Disciplines

Statistical Methodology | Statistical Models | Transportation

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