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The effect of human mobility and control measures on traffic safety during COVID-19 pandemic

Author

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  • Jie Zhang
  • Baoheng Feng
  • Yina Wu
  • Pengpeng Xu
  • Ruimin Ke
  • Ni Dong

Abstract

As mobile device location data become increasingly available, new analyses are revealing the significant changes of mobility pattern when an unplanned event happened. With different control policies from local and state government, the COVID-19 outbreak has dramatically changed mobility behavior in affected cities. This study has been investigating the impact of COVID-19 on the number of people involved in crashes accounting for the intensity of different control measures using Negative Binomial (NB) method. Based on a comprehensive dataset of people involved in crashes aggregated in New York City during January 1, 2020 to May 24, 2020, people involved in crashes with respect to travel behavior, traffic characteristics and socio-demographic characteristics are found. The results show that the average person miles traveled on the main traffic mode per person per day, percentage of work trip have positive effect on person involved in crashes. On the contrary, unemployment rate and inflation rate have negative effects on person involved in crashes. Interestingly, different level of control policies during COVID-19 outbreak are closely associated with safety awareness, driving and travel behavior, and thus has an indirect influence on the frequency of crashes. Comparing to other three control policies including emergence declare, limits on mass gatherings, and ban on all nonessential gathering, the negative relationship between stay-at-home policy implemented in New York City from March 20, 2020 and the number of people involved crashes is found in our study.

Suggested Citation

  • Jie Zhang & Baoheng Feng & Yina Wu & Pengpeng Xu & Ruimin Ke & Ni Dong, 2021. "The effect of human mobility and control measures on traffic safety during COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-9, March.
    • Handle: RePEc:plo:pone00:0243263
    DOI: 10.1371/journal.pone.0243263
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    Citations

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    Cited by:

    1. Wang Xiang & Li Chen & Qunjie Peng & Bing Wang & Xiaobing Liu, 2022. "How Effective Is a Traffic Control Policy in Blocking the Spread of COVID-19? A Case Study of Changsha, China," IJERPH, MDPI, vol. 19(13), pages 1-17, June.
    2. Yakup Çelikbilek & Sarbast Moslem, 2023. "A grey multi criteria decision making application for analyzing the essential reasons of recurrent lane change," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 916-941, June.
    3. Xingpei Yan & Zheng Zhu, 2021. "Quantifying the impact of COVID-19 on e-bike safety in China via multi-output and clustering-based regression models," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-15, August.
    4. Haruka Kato & Daisuke Matsushita, 2021. "Changes in Walkable Streets during the COVID-19 Pandemic in a Suburban City in the Osaka Metropolitan Area," Sustainability, MDPI, vol. 13(13), pages 1-20, July.
    5. Yongji Ma & Jinliang Xu & Chao Gao & Chenwei Gu & Xiaohui Tong, 2022. "The Limited Responses of Provincial Expressway Network Operation Quality to the Impact of COVID-19: Taking Shaanxi Province as an Example," Sustainability, MDPI, vol. 14(17), pages 1-22, August.
    6. Jill Atkins & Federica Doni & Andrea Gasperini & Sonia Artuso & Ilaria Torre & Lorena Sorrentino, 2023. "Exploring the Effectiveness of Sustainability Measurement: Which ESG Metrics Will Survive COVID-19?," Journal of Business Ethics, Springer, vol. 185(3), pages 629-646, July.

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