COVID-19 was declared a pandemic since March 2020. Different state and local agencies and private employers introduced unprecedented public health measures to contain and reduce its spread and protect the public. These measures included closures of government offices, businesses, major factories, and educational institutions. As a results, driving patterns and behaviors in the United States changed significantly during the COVID-19 pandemic. An analysis of traffic patterns during this period has identified that reduction in the miles traveled has a significant negative correlation with COVID-19 cases and deaths across the USA. Preliminary statistics in the US suggest an increase in fatal crashes over the period of the lockdown in comparison to the same period in previous years. Moreover, while total crashes are down, motor vehicle crashes involving non-motorists became more prevalent. At the same time, non-motorist traffic has increased while motor vehicle traffic and crashes have shifted to the local systems. The main goal of this research is to perform a comprehensive evaluation of the changes in travel patterns, and crash risk factors and severity during COVID-19 pandemic and compare crash characteristics to those immediately before the pandemic at different temporal and spatial levels. This includes developments of a database of crash reports in Texas, calculation of crash counts and rates, acquiring traffic volumes, and identifying high risk and/or vulnerable groups during the shutdown such as long-haul truck drivers, bicyclists, and pedestrians. The analysis will also include the types of collisions, e.g., head-on, fender-bender, etc. Additionally, injury severity analyses will be performed to understand the association between various crash factors and crash outcomes before and after the lockdown order. This will be done to assess whether the factors that influenced crash outcomes differed before and during the pandemic. Addressing the needs of vulnerable road users requires that transportation agencies understand how their risks might have changed during the COVID-19 pandemic. The impacts of the changes in mobility and travel during the COVID-19 pandemic will be investigated through detailed analysis of their impact on the spatiotemporal patterns of crashes in a number demographically different counties in Texas. The results can provide useful lessons for road safety improvements during extreme events that may require statewide lockdown, as has been done with the COVID-19 pandemic and offers the opportunity for traffic safety professionals to plan appropriate countermeasures for a new COVID-19 wave or even future pandemics. Moreover, the research findings are expected to provide a data-driven foundation to prioritize road safety strategies in order to minimize the effects of the COVID-19 pandemic on road safety. In order to provide an efficient solution to the research problem, the research team aims to carry out the tasks outlined below: (1) The research team will first undertake a thorough review of published literature on COVID-19 pandemic impacts and related safety countermeasures, a review of changes in traffic patterns, speeds and times, an analysis of changes in crash and injury counts and rates, and a survey of transportation officials. Available past research and reports of a related nature, from Texas, Region 6, across the nation, and internationally, will be reviewed. Some of these resources will be listed and individually described elsewhere in this proposal. (2) The research team will compile operational and safety data from sources such as the Texas Crash Records Information System (CRIS), the national Fatality Analysis and Reporting System (FARS) for other states of Region 6, which has far more specialized detail on fatal crashes, Texas Department of State Health Services records, and crash narratives. (3) The research team will use data mining to examine space-time indicators that may reveal information about the correlation between changes in crash counts and severity and traffic volumes, common characteristics of the built environment that contribute to unsafe actions and conditions, and other factors. (4) The research team will use different data collection techniques to understand road user's behavior and review crash narratives and diagrams. These observations will not only be helpful in the analysis of risk factors, but also provide a framework that guides decision-making throughout the entire process, from identifying a problem to implementing a countermeasure. (5) The research team will employ spatial analysis techniques including Geographic Information System (GIS)-based methods to visualize the spatial differences in crash density and crash severity patterns between and pre-pandemic and COVID-19 pandemic periods, non-parametric statistic methods (such as Kruskal–Wallis) to examine whether the changes in crash densities and severity are statistically significant, and models, such as the negative binomial regression-based approach, to identify the significant socio-demographic and traffic-related factors contributing to crash count and severity changes during the COVID-19 pandemic.
|Effective start/end date
|12/2/16 → 9/30/24
- U.S. Department of Transportation: $108,000.00
- U.S. Department of Transportation: $112,235.00
- U.S. Department of Transportation: $106,006.00
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