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Assessing driver behavior using shrp2 adverse weather data
Institution:1. Eco-Transportation and Alternative Technologies, Center for Infrastructure-Based Safety Systems, Virginia Tech Transportation Institute, 3500 Transp. Research Plaza, Blacksburg, VA 24061, United States;2. Center for Infrastructure-Based Safety Systems, Virginia Tech Transportation Institute, 3500 Transp. Research Plaza, Blacksburg, VA 24061, United States;3. Virginia Tech Transportation Institute, Blacksburg, VA, USA;1. Technische Universität Chemnitz, 09107 Chemnitz, Germany;2. Technische Universität Dresden, 01062 Dresden, Germany;3. BMW Group, 80788 München, Germany;1. Department of Epidemiology, University of Iowa, 145 N. Riverside Dr, Iowa City, IA 52242, United States;2. Injury Prevention Research Center, University of Iowa, 145 N. Riverside Dr, Iowa City, IA 52242, United States;3. University of Iowa, Department of Occupational and Environmental Health, 145 N. Riverside Dr, Iowa City, IA 52242, United States;1. University of Wyoming, Department of Civil & Architectural Engineering, 1000 E University Ave, Dept. 3295, Laramie, WY 82071, United States;2. FHWA Turner Fairbank Highway Research Center, 6300 Georgetown Pike, McLean, VA 22101, United States;3. Deep Numerics, LLC, 3317 Curving Oaks Way, Orlando, FL 32820, United States;1. Alabama Transportation Institute, The University of Alabama, Tuscaloosa, AL 35487, United States;2. Kentucky Transportation Center, University of Kentucky, Lexington, KY 40506, United States;3. Transportation Research Center, Civil Engineering, University of Nevada, Las Vegas, NV 89154, United States;1. National Institute for Occupational Safety and Health (NIOSH), Centers for Disease Control and Prevention (CDC), 1090 Tusculum Ave. MS C-10, Cincinnati, OH 45226, United States;2. RTI International, 3040 Cornwallis Road, Research Triangle Park, NC 27709, United States
Abstract:IntroductionThis study explored how drivers adapt to inclement weather in terms of driving speed, situational awareness, and visibility as road surface conditions change from dry to slippery and visibility decreases. The proposed work mined existing data from the SHRP 2 NDS for drivers who were involved in weather-related crash and near-crash events. Baseline events were also mined to create related metadata necessary for behavioral comparisons. Methods: Researchers attempted, to the greatest extent possible, to match non-adverse-weather driving scenarios that are similar to the crash and near-crash event for each driver. The ideal match scenario would be at a day prior to the crash during non-adverse weather conditions having the same driver, at the same time of day, with the same traffic level on the same road on which the crash or near-crash occurred. Once the matched scenarios have been identified, a detailed analysis will be performed to determine how a driver’s behavior changed from normal driving to inclement-weather driving. Results: Data collected indicated that, irrespective of site location (i.e., state), most crashes and near-crashes occurred in rain, with only about 12% occurring in snowy conditions. Also, the number of near-crashes was almost double the number of crashes showing that many drivers were able to avoid a crash by executing an evasive maneuver such as braking or steering. Conclusions: Most types of near crashes were rear-end and sideswipe avoidance epochs, as the drivers may have had a difficult time merging or trying to change lanes due to low visibility or traffic. Hard braking combined with swerving were the most commonly used evasive maneuvers, occurring when drivers did not adjust their speeds accordingly for specific situations. Practical applications: Results from this study are expected to be utilized to educate and guide drivers toward more confident and strategic driving behavior in adverse weather.
Keywords:Near-crash  Adverse weather  Crash  Slippery  Event
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