01661277

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In recent decades, electric bicycles have experienced increasing popularity in China. Yet despite their huge benefit to urban mobility, they also have become a serious traffic safety problem with a significant number of causalities. This problem is partially attributed to the lack of non- motorized vehicle guidelines in crash hot-zone and problem identification, and routine traffic enforcement is not well-oriented to these vehicles. In order to bridge this gap, this research aims at providing information on the key issues with electric bicycle safety management. Electric bicycle crash data, road network features, population and land use of 213 sub-districts in Shanghai were collected as independent variables. Based upon the collected data, macro-level safety studies were carried out. Historical crash records were divided into two categories as per their severity levels: fatal and injury (FI) crashes and property damage only (PDO) crashes. In order to accommodate the correlation between crashes of different severity levels as well as spatial correlation between the studied units, a Multivariate Poisson Log-normal (MVPLN) Conditional Autoregressive (CAR) model was developed to explore the relationship between crashes at different severity levels and their corresponding independent variables. The authors further calculated a Potential for Safety Improvements (PSI) for each sub-district and used it for hot- zone identification. Finally, an integrated screening was conducted and safety problems were identified for the major hot-zone classifications studied. The results show that the hot-zones of FI electric bicycle crashes areas are more concentrated in urban fringe compared to those of PDO crashes. The most frequently reported causes of crashes is motorized vehicles failing or refusing to yield. Based on the findings, a few corresponding countermeasures are further proposed.

This paper was sponsored by TRB committee ANF20 Standing Committee on Bicycle Transportation.

18-04146

English

10p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References (11) ; Tables

Bicycles; Crash analysis; Crash injuries; Electric vehicles; High risk locations; Safety management; Urban areas

Shanghai (China)

Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment

Transportation Research Board Annual Meeting 2018 Paper #18-04146

TRIS, TRB, ATRI

Jan 8 2018 11:01AM