Crash histories,safety perceptions,and attitudes among Virginia bicyclists |
| |
| Affiliation: | 1. Kidney Two Families, Heilongjiang Academy of Chinese Mediceal Sciences, 142 Sanfu Street, Xiangfang District, Harbin, China;2. School of Management, Harbin Institution of Technology, 13 Fayuan Street, Nangang District, Harbin, China;3. Liver and Spleen and Stomach Diseases, Heilongjiang Academy of Chinese Medical Sciences, 142 Sanfu Street, Xiangfang District, China;4. Leeds University Business School, University of Leeds, LS6 1AN, Leeds, United Kingdom;1. CHALMERS - University of Technology, Dept. of Mechanics and Maritime Sciences (M2), SAFER - Lindholmspiren 3, floor 2, 417 56 Göteborg, Sweden;2. Department of Mechanical and Aerospace Engineering, University of California Davis, Davis, CA 95616, United States;3. BioMechanical Engineering, Delft University of Technology, Mekelweg 2, NL 2628, CD, Delft, the Netherlands;1. Centre for Accident Research & Road Safety – QLD, Queensland University of Technology, K Block, 130 Victoria Park Road, Kelvin Grove, QLD 4059, Australia;2. Institute for Road Safety Research (SWOV), Bezuidenhoutseweg 62, 2594 AW, The Hague, the Netherlands;3. Royal HaskoningDHV, Laan 1914 no 35, 3818 EX, Amersfoort, the Netherlands;4. CROW, Hora plantsoon 18, 6717 LT, Ede, the Netherlands;5. Centraal Instituut toetsontwikkeling (CITO), Amsterdamseweg 13, 6814 CM, Arnhem, the Netherlands |
| |
| Abstract: | IntroductionCycling injury and fatality rates are on the rise, yet there exists no comprehensive database for bicycle crash injury data.MethodWidely used for safety analysis, police crash report datasets are automobile-oriented and widely known to under-report bicycle crashes. This research is one attempt to address gaps in bicycle data in sources like police crash reports. A survey was developed and deployed to enhance the quality and quantity of available bicycle safety data in Virginia. The survey captures bicyclist attitudes and perceptions of safety as well as bicycle crash histories of respondents.ResultsThe results of this survey most notably show very high levels of under-reporting of bicycle crashes, with only 12% of the crashes recorded in this survey reported to police. Additionally, the results of this work show that lack of knowledge concerning bicycle laws is associated with lower levels of cycling confidence. Count model results predict that bicyclists who stop completely at traffic signals are 40% less likely to be involved in crashes compared to counterparts who sometimes stop at signals. In this dataset, suburban and urban roads with designated bike lanes had more favorable injury severity profiles, with lower percentages of severe and minor injury crashes compared to similar roads with a shared bike/automobile lane or no designated bike infrastructure. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
