Kitty Hancock Analyzes Reckless Driving Related Crashes
As a Resutl of the Stay-At-Home Directive in Virginia
KITTY HANCOCK ANALYZES RECKLESS DRIVING RELATED CRASHES AS A RESULT OF THE STAY-AT-HOME DIRECTIVE IN VIRGINIA
Governor Northam issued a Declaration of Emergency on March 12, 2020, followed by a stay-at-home order effective March 30, 2020 for the Commonwealth of Virginia. As a result, Virginia saw a substantial reduction in traffic, which also reduced the number of vehicle crashes.
Virginia Tech researchers, including Kathleen Hancock, partnered with the Virginia Department of Motor Vehicles (DMV) to understand the reduction and to identify driver and pedestrian behaviors and their consequences as a result of the pandemic. While total crashes have decreased, one of the more concerning aspects during the pandemic is that, although fatal crashes dropped during the stay-at-home order, they now are nearly equal to the same period in 2019. Another disturbing consequence of reduced traffic on the roads is the apparent increase in speeds and reckless driving of some drivers. One of the goals of this analysis is to evaluate whether and how this translates to increased numbers of speed-related crashes and crash severity.
This analysis fits in with projects that Hancock and her team have already been working on. She works with undergraduate and graduate students in civil engineering and with the Center for Geospatial Information Technologies (CGIT) on campus to geocode and supplement the crash data and to solve problems such as identifying the highest crash intersections and using data mining techniques to extract information from the text that police officers include in their reports about the crashes and why they occur. This information is used for on-demand support when officials ask for more information about a crash and what can be done to avoid a similar circumstance in the future.
The team developed a methodology and tool to locate all reported crashes in Virginia and have been providing standardized crash location for nearly 10 years. They provide a series of reports that DMV distributes to their stakeholders and the legislature identifying types of crashes based on human factors such as alcohol use and speeding. They partner with the Highway Safety Office to provide requested information including summarizing characteristics of drivers and pedestrians involved in crashes. These same methodologies are being applied to the analysis of pandemic-related traffic patterns and crashes.
The team continues to analyze the data to see if trends have changed after the stay-at-home order was lifted and as more commuters return to work.