The cycling research page here at Aushiker.com has been updated with three new papers looking at safe passing laws, bicycle riding related injuries and a look at the effect of neighbourhoods on your bicycle riding. The details of the papers and abstracts follow.
Cycling Research Updates #1: Added in the section: Cycling Research – Cyclists and Motorist Interaction
Love, D. C., Breaud, A. Burns, S., Margulies, J., Romano, M. & Lawrence, R. Is the three-foot bicycle passing law working in Baltimore, Maryland? Accident Analysis and Prevention, doi:
Maryland (MD) recently became one of fourteen states in the United States to enact a traffic law requiring motor vehicles to pass bicyclists at a distance of greater than three feet. To our knowledge, motorist compliance with the law has never been assessed. This study measured the distance between overtaking motor vehicles and cyclists [e.g. vehicle passing distance (VPD)], to develop baseline metrics for tracking implementation of the three-foot passing law in Baltimore, MD and to assess risk factors for dangerous passes. During September and October 2011, cyclists (n = 5) measured VPD using a previously published video technique (Parkin and Meyers, 2010). Cyclists logged a total of 10.8 h of video footage and 586 vehicle passes on 34 bicycle commuting trips. The average trip lasted 19.5 ± 4.9 min and cyclists were passed on average 17.2 ± 11.8 times per trip. VPDs of three feet or less were common when cycling in standard lanes (17%; 78 of 451 passes) and lanes with a shared lane marking (e.g. sharrows) (23%; 11 of 47 passes). No passes of three feet or less occurred in bicycle lanes (0 of 88 passes). A multiple linear regression model was created, which explained 26% of the variability in VPD. Significant model variables were lane width, bicycle infrastructure, cyclist identity, and street identity. Interventions, such as driver education, signage, enforcement, and bicycle infrastructure changes are needed to influence driving behavior in Baltimore to increase motorist compliance with the three-foot law.
Cycling Research Updates #2: Added in the section: Cycling and Pedestrian Injury Research
Cripton, P.A., Shen, H., Brubacher, J. R., Chipman, M., Friedman, S. M., Harris, M. A., Winters, M., Reynolds, C. C. O, Cusimano, M.D., Babul, S. & Teschke, K. Severity of urban cycling injuries and the relationship with personal, trip, route and cash characteristics: Analyses using four severity metrics. BMJ Open, 5. doi:10.1136/bmjopen-2014-006654
To examine the relationship between cycling injury severity and personal, trip, route and crash characteristics.
Data from a previous study of injury risk, conducted in Toronto and Vancouver, Canada, were used to classify injury severity using four metrics: (1) did not continue trip by bike; (2) transported to hospital by ambulance; (3) admitted to hospital; and (4) Canadian Triage and Acuity Scale (CTAS). Multiple logistic regression was used to examine associations with personal, trip, route and crash characteristics.
Of 683 adults injured while cycling, 528 did not continue their trip by bike, 251 were transported by ambulance and 60 were admitted to hospital for further treatment. Treatment urgencies included 75 as CTAS=1 or 2 (most medically urgent), 284 as CTAS=3, and 320 as CTAS=4 or 5 (least medically urgent). Older age and collision with a motor vehicle were consistently associated with increased severity in all four metrics and statistically significant in three each (both variables with ambulance transport and CTAS; age with hospital admission; and motor vehicle collision with did not continue by bike). Other factors were consistently associated with more severe injuries, but statistically significant in one metric each: downhill grades; higher motor vehicle speeds; sidewalks (these significant for ambulance transport); multiuse paths and local streets (both significant for hospital admission).
In two of Canada’s largest cities, about one-third of the bicycle crashes were collisions with motor vehicles and the resulting injuries were more severe than in other crash circumstances, underscoring the importance of separating cyclists from motor vehicle traffic. Our results also suggest that bicycling injury severity and injury risk would be reduced on facilities that minimise slopes, have lower vehicle speeds, and that are designed for bicycling rather than shared with pedestrians
Cycling Research Updates #3: Added in the section: Cycling Research – Participation in Cycling
Wang, C., Akar, G., Guldmann, J. (2015). Do your neighbours affect your bicycling choice? A spatial profit model for bicycling to The Ohio State University. Journal of Transport Geography, 42, 122-130. doi:10.1016/j.jtrangeo.2014.12.003
Neighborhood social effects have recently become a focus of interest in transportation research, whereby transportation mode choice is not only affected by an individual’s characteristics and transportation system conditions, but also by the mode choices of that individual’s social neighbors. This study supports the neighborhood social effects argument, using a spatial econometrics approach and data from The Ohio State University (OSU) 2012 Campus Transportation Survey. A spatial probit model of commuters’ mode choices (bicycling versus non-bicycling) is estimated, accounting for spatial autocorrelation. The results show that the more OSU-affiliated bicycle riders are residing around an individual OSU commuter, the more attractive bicycling becomes, controlling for other factors such as gender, status, proximity to campus, bicycle infrastructure and attitudes. The results indicate that students and males are more likely to commute by bicycles. The probability of choosing bicycles decreases with distance from campus. In addition, proximity to bicycle infrastructure and physical environment both encourage respondents to bicycle. Feeling of safety, travel cost and concern for the environment also affect bicycling choice.