How bicycle level of traffic stress correlate with reported cyclist accidents injury severities: A geospatial and mixed logit analysis. (November 2017)

• Record Type: Journal Article
• Authors: Chen, Chen; Anderson, Jason C.; Wang, Haizhong; Wang, Yinhai; Vogt, Rachel; Hernandez, Salvador
• Is Part Of: Accident analysis and prevention. Volume 108(2017)
• Page Start: 234
• Page End: 244
• Publication Date: 2017-11
• Subjects: Bicycle level of traffic stress -- Bicycle crash severities -- Geospatial mapping -- Mixed logit model; Accidents -- Prevention -- Periodicals; Accident Prevention -- Periodicals; Accidents -- Prévention -- Périodiques; 363.106
• DOI: 10.1016/j.aap.2017.09.001
• Languages: English
• ISSNs: 0001-4575

Abstract

Highlights: Correlation between level of traffic stress (LTS) and bicycle crash severity is investigated. Mixed logit model and geospatial analysis are used to assess correlation. Higher LTS was found to impact injury severity outcomes. LTS and crowd-sourcing data can assist with bicycle route choice estimation. Recommendations regarding LTS and bicycle safety improvements are provided. Abstract: Transportation agencies need efficient methods to determine how to reduce bicycle accidents while promoting cycling activities and prioritizing safety improvement investments. Many studies have used standalone methods, such as level of traffic stress (LTS) and bicycle level of service (BLOS), to better understand bicycle mode share and network connectivity for a region. However, in most cases, other studies rely on crash severity models to explain what variables contribute to the severity of bicycle related crashes. This research uniquely correlates bicycle LTS with reported bicycle crash locations for four cities in New Hampshire through geospatial mapping. LTS measurements and crash locations are compared visually using a GIS framework. Next, a bicycle injury severity model, that incorporates LTS measurements, is created through a mixed logit modeling framework. Results of the visual analysis show some geospatial correlation between higher LTS roads and "Injury" type bicycle crashes. It was determined, statistically, that LTS has an effect on the severity level of bicycle crashes and high LTS can have varying effects on severity outcome. However, it is recommended that further analyses be conducted to better understand the statistical significance and effect of LTS on injury severity. As such, this research will validate the use of LTS as a proxy for safety risk regardless of the recorded bicycle crash history. This research will help identify the clustering patterns of bicycle crashes on high-risk corridors and, therefore, assist with bicycle route planning and policy making. This paper also suggests low-cost countermeasures or treatments that can be implemented to address high-risk areas. Specifically, with the goal of providing safer routes for cyclists, such countermeasures or treatments have the potential to substantially reduce the number of fatalities and severe injuries.