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  • Title: Using SHRP2 naturalistic driving data to examine driver speeding behavior.
    Author: Richard CM, Lee J, Atkins R, Brown JL.
    Journal: J Safety Res; 2020 Jun; 73():271-281. PubMed ID: 32563403.
    Abstract:
    PROBLEM: Speeding-related crashes continue to be a serious problem in the United States. According to the National Highway Traffic Safety Administration, 26% of all fatal crashes in 2017 had speeding as a contributing factor. METHOD: Vehicle speed data recorded during the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study were analyzed to identify the frequency of speeding episodes. Up to 100 trips were sampled from 2,910 individual drivers aged 16-64. Vehicle speed data from individual trips were parsed into continuous speeding episodes (SEs) and Free-Flow Episodes (FFEs), which approximated opportunities to speed. RESULTS & DISCUSSION: Driving 10 mph above the posted speed limit (PSL) was common, and 99.8% of drivers had at least one occurrence SE within their trip sample, yielding an average of 2.75 SEs per trip (623,202 SEs in total). The analysis focused on a subset of higher-speed SEs in which the vehicle reached speeds of at least 15 mph above the PSL during the SE (71,113 SEs in total). Average maximum speeds for most higher-speed SEs ranged between 12 mph to 15 mph above the PSL, and most also lasted less than 2 min. Most drivers spent less than 5% of the FFE time speeding, and only a small number of drivers spent more than 10% of the time speeding. There was also a clear trend towards the younger group having higher overall percentages of SE time relative to FFE time. Practical Applications: The methods and measures developed in this study provide the foundation for future analyses to determine if there are different types of speeding that vary in terms of risky characteristics, and further, if certain drivers are more likely to engage in riskier speeding behavior. Identifying higher-risk speeders is an important step for developing countermeasures and strategies targeting drivers that are at greatest risk of speed-related crashes.
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