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Safety in Numbers and Safety in Congestion for Bicyclists and Motorists at Urban Intersections

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Abstract

This study assesses the estimated crashes per bicyclist and per vehicle as a function of bicyclist and vehicle traffic, and tests whether greater traffic reduces the per-car crash rate. We present a framework for comprehensive bicyclist risk assessment modeling, using estimated bicyclist flow per intersection, observed vehicle flow, and crash records. Using a two-part model of crashes, we reveal that both the annual average daily traffic and daily bicyclist traffic have a diminishing return to scale in crashes. This accentuates the positive role of safety in numbers. Increasing the number of vehicles and cyclists decelerates not only the probability of crashes, but the number of crashes as well. Measuring the elasticity of the variables, it is found that a 1% increase in the annual average daily motor vehicle traffic increases the probability of crashes by 0.14% and the number of crashes by 0.80%. However, a 1% increase in the average daily bicyclist traffic increases the probability of crashes by 0.09% and the number of crashes by 0.50%. The saturation point of the safety in numbers for bicyclists is notably less than for motor vehicles. Extracting the vertex point of the parabola functions examines that the number of crashes starts decreasing when daily vehicle and bicyclist traffic per intersection exceed 29,568 and 1,532, respectively.

Suggested Citation

  • Kristin Carlson & Alireza Ermagun & Brendan Murphy & Andrew Owen & David Levinson, 2017. "Safety in Numbers and Safety in Congestion for Bicyclists and Motorists at Urban Intersections," Working Papers 000165, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:safetyinnumbers-bikes
    DOI: http://dx.doi.org/10.1177/0361198119846480
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    File URL: http://hdl.handle.net/11299/189809
    File Function: First version, 2017
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    References listed on IDEAS

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    1. Reserve Bank of New Zealand, 2011. "For the record," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 74, pages 51-60, June.
    2. Lowry, Michael, 2014. "Spatial interpolation of traffic counts based on origin–destination centrality," Journal of Transport Geography, Elsevier, vol. 36(C), pages 98-105.
    3. Reserve Bank of New Zealand, 2011. "For the record," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 74, pages 1-7, December.
    4. Reserve Bank of New Zealand, 2011. "For the record," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 74, pages 46-56, September.
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    More about this item

    Keywords

    Safety; Bicyclist crashes; Returns to scale; Road intersection;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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