Risk Factors for Young Drivers in Fatal and Non-Fatal Crashes: Supplementary Report

Mastromatto, Tia; Quinones, Tatiana; Lan, Bo; Srinivasan, Raghavan; Lococo, Kathy H.; Staplin, Loren · 2022 · ROSA P / United States. Department of Transportation. National Highway Traffic Safety Administration

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Summary

This supplementary report, published by the National Highway Traffic Safety Administration (NHTSA) in 2022, addresses the persistent safety risks associated with young drivers (ages 14–20). While Graduated Driver Licensing (GDL) programs have successfully reduced crash rates for 16- and 17-year-olds, they have been less effective in ensuring safe behavior once drivers age out of these restrictions. The study aims to provide detailed analytical results to inform potential enhancements to GDL and driver education programs by identifying specific risk factors in both fatal and non-fatal crashes. The research utilized two primary datasets: the Fatality Analysis Reporting System (FARS) for fatal crashes from 2013 to 2017, and the Strategic Highway Research Program’s Naturalistic Driving Study (SHRP2 NDS) for non-fatal events. For FARS data, the analysis included 12,998 qualifying crashes, comparing young drivers (cohorts aged 14–20) against a reference group of 35-year-old drivers. The methodology employed quasi-induced exposure analyses to calculate Crash Involvement Ratios (CIRs) for multi-vehicle crashes where only one driver had a contributing factor. Logistic regression was used to determine if CIRs for young drivers differed significantly from the 35-year-old reference group. For SHRP2 data, the study analyzed 1,113 multi-vehicle events, calculating CIRs based on age and driving experience in half-year increments, though statistical significance testing was not performed due to insufficient sample sizes for comparison. The findings present descriptive statistics and CIR calculations across various driver, vehicle, roadway, and crash characteristics. In FARS single-vehicle fatal crashes, approximately three-quarters of drivers were male. Police-reported alcohol involvement increased with age, affecting 6% of 16-year-olds and over 25% of drivers aged 20 and older. Passenger presence varied significantly by age; nearly half of drivers under 16 had more than two passengers, whereas nearly half of young drivers overall were alone. Distraction was reported in 10% of crashes, though data were missing for about one-third of drivers. The report provides extensive frequency counts and CIR values in appendices, highlighting specific variables where young drivers showed significantly higher involvement ratios compared to the 35-year-old reference group, such as in certain crash maneuvers and roadway conditions. The significance of this report lies in its comprehensive granular data, which supports the refinement of GDL laws and driver education curricula. By identifying specific conditions and behaviors where young drivers are disproportionately involved in crashes, policymakers and educators can target interventions more effectively. The inclusion of both fatal and non-fatal data allows for a broader understanding of risk trajectories as drivers gain experience, addressing the gap in safety outcomes observed after drivers exit GDL restrictions.

Key finding

The report provides detailed crash involvement ratios and descriptive statistics for young drivers aged 14 to 20 compared to 35-year-old drivers, utilizing FARS data for fatal crashes and SHRP2 NDS data for naturalistic driving events to identify risk factors associated with crash involvement.

Methodology

dataset

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• novice drivers
• incidence prevalence
• sex gender
• demographic disparities
• passenger effects
• pre crash contributing factors

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: crash risk outcomes, observational prevalence
• Methodological Resource: dataset resource