School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China.
National United Engineering Laboratory of Integrated and Intelligent Transportation, Chengdu, China.
PLoS One. 2021 Mar 8;16(3):e0243263. doi: 10.1371/journal.pone.0243263. eCollection 2021.
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.
随着移动设备位置数据的日益普及，新的分析显示，当意外事件发生时，移动模式发生了显著变化。由于地方和州政府采取了不同的控制政策，COVID-19 疫情极大地改变了受影响城市的流动行为。本研究使用负二项（NB）方法，调查了 COVID-19 对涉及车祸人数的影响，同时考虑了不同控制措施的强度。本研究基于 2020 年 1 月 1 日至 2020 年 5 月 24 日期间在纽约市汇总的涉及车祸人员的综合数据集，研究了与旅行行为、交通特征和社会人口特征有关的涉及车祸人员。结果表明，主要交通方式上人均每日行驶里程、工作出行比例对涉及车祸人员有正向影响。相反，失业率和通货膨胀率对涉及车祸人员有负向影响。有趣的是，COVID-19 疫情期间不同级别的控制政策与安全意识、驾驶和旅行行为密切相关，因此对车祸频率有间接影响。与其他三种控制政策（包括宣布紧急状态、限制大规模集会和禁止所有非必要集会）相比，我们的研究发现，2020 年 3 月 20 日纽约市实施的就地避难政策与涉及车祸人数呈负相关关系。
