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Using bicycle app data to develop Safety Performance Functions (SPFs) for bicyclists at intersections: A generic framework

Author

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  • Chen, Chen
  • Wang, Haizhong
  • Roll, Josh
  • Nordback, Krista
  • Wang, Yinhai

Abstract

More accurate predictions of bicycle crashes can increase the return on investment from bicycle safety initiatives. One useful tool to understand the association between critical factors and crashes is Safety Performance Functions (SPFs), but most U.S. studies have developed SPFs for motorized vehicles not for bicycles. The objective of this study is to develop SPFs for intersections in a medium- and a large-sized city using bicycle app data (i.e., Strava data), leveraging the rising popularity of social media and mobile phones. Our case studies are from the Portland and Eugene-Springfield metropolitan areas with sizable bike population, which alleviates the challenge of insufficient bicycle volume and crash data. Specifically, in this research (1) bicycle SPFs are created for intersections in medium- and large-sized cities; (2) affordable bicycle app volume data, is used as a surrogate for exposure; (3) bicycle app data is shown to be correlated with automatic bike count station data (p<0.01); (4) bicycle app count shows a significant association with intersection crashes (p<0.01); (5) a general framework for building bicycle SPFs is developed for jurisdictions and the corresponding model is validated to demonstrate predictive ability; and (6) recommendations on infrastructure design and non-motorized policy making are provided with the goal of developing a safer environment for bicyclists.

Suggested Citation

  • Chen, Chen & Wang, Haizhong & Roll, Josh & Nordback, Krista & Wang, Yinhai, 2020. "Using bicycle app data to develop Safety Performance Functions (SPFs) for bicyclists at intersections: A generic framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 1034-1052.
    • Handle: RePEc:eee:transa:v:132:y:2020:i:c:p:1034-1052
    DOI: 10.1016/j.tra.2019.12.034
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    References listed on IDEAS

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    1. Wang, Haizhong & Palm, Matthew & Chen, Chen & Vogt, Rachel & Wang, Yiyi, 2016. "Does bicycle network level of traffic stress (LTS) explain bicycle travel behavior? Mixed results from an Oregon case study," Journal of Transport Geography, Elsevier, vol. 57(C), pages 8-18.
    2. Börjesson, Maria & Eliasson, Jonas, 2012. "The value of time and external benefits in bicycle appraisal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 673-683.
    3. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    4. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    5. Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
    6. Bofinger, Peter & Haas, Thomas, 2018. "A simple microeconomic model for the analysis of Vollgeld," W.E.P. - Würzburg Economic Papers 99, University of Würzburg, Department of Economics.
    7. Jean Beuve & Stéphane Saussier & Julie de Brux, 2018. "An Economic Analysis of Public-Private Partnerships," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02139523, HAL.
    8. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    9. Jestico, Ben & Nelson, Trisalyn & Winters, Meghan, 2016. "Mapping ridership using crowdsourced cycling data," Journal of Transport Geography, Elsevier, vol. 52(C), pages 90-97.
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    Cited by:

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    2. Chen Chen & Alireza Mostafizi & Haizhong Wang & Dan Cox & Lori Cramer, 2022. "Evacuation behaviors in tsunami drills," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 845-871, May.

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