Highlights Naturalistic driving data was used to assess the likelihood of speeding behaviors. Automated processes provided speed limit information. Speeding behavior frequent at lower speed limits and predicted by subjective metrics.
Abstract Speeding behaviors are quite common and are known to affect the risk and severity outcomes of vehicular crashes. Naturalistic driving data allows for the direct observation of speeding and the development of evidence-based causal structures for this behavior. This limits biases associated with self-reported speeding prevalence, allowing for more precise speeding measures than post-crash investigations and for the evaluation of driver attributes associated with speeding across a wide variety of locations and road types. Data from the Second Strategic Highway Research Program Naturalistic Driving Study were used to identify speeding events that were aggregated based on their duration and degree of speeding above the posted speed limit. The events were summarized as a likelihood of speeding metric for each trip in the dataset. These likelihood of speeding measurements were also aggregated across drivers and compared, using a beta binomial regression model, to driver questionnaire answers that addressed drivers’ perception of their speeding as well as different driver-specific factors that are suspected of having an influence on speeding behaviors. Results showed that, consistent with past studies, age and gender significantly influenced the likelihood of speeding. For age, the odds of speeding exhibited a significant downward trend across increasing age groups; 16–24 year olds exhibited odds of speeding that were 1.5 times the odds of drivers that were 80 or more years old. For gender, males exhibited larger odds of speeding than females (1.1 times larger). In addition, the odds of speeding were larger at lower posted speed limits. The odds of speeding in 10–20 mph zones were 9.5 times the odds of zones with speed limits greater than 60 mph, implying that drivers may be unaware of the risks associated with speeding in low speed limit areas. Several questionnaire answers related to drivers’ perception of speeding were also predictive of the likelihood of speeding.
Factors modifying the likelihood of speeding behaviors based on naturalistic driving data
2021-06-15
Article (Journal)
Electronic Resource
English
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