Targeted Reporting of Speeding-Related Crashes

NHTSA · 2020 · ROSA P / United States. Department of Transportation. Federal Highway Administration

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Summary

This paper addresses the misclassification of speeding-related crashes in Arizona, specifically focusing on the inconsistent coding of the "Speed Too Fast for Conditions" (STFC) field on crash reports. The research was motivated by the realization that historical coding practices conflated actual speeding issues with behavioral impairments, such as driving under the influence (DUI), distraction, or fatigue. Because officers often interpreted "conditions" to include the driver’s behavioral state, crashes involving impaired drivers traveling below the posted speed limit were frequently coded as STFC. This misclassification hindered the effective allocation of safety resources, as countermeasures designed for speeding, such as dynamic speed feedback signs or lane narrowing, are ineffective against impairment-related crashes. The study utilizes a case study approach centered on Arizona Department of Transportation (ADOT) data from 2012 to 2016. The authors analyzed crash report data to quantify the extent of misclassification and evaluated the impact of updating coding instructions. The primary methodological intervention was the revision of crash form guidelines to explicitly exclude behavioral conditions from the STFC definition. The new instructions define STFC strictly as traveling at a speed unsafe for road, weather, or traffic conditions, explicitly stating that it does not include distraction, impairment, fatigue, or other violations that make any speed unreasonable. This change aimed to ensure that crashes driven by human factors are coded as impairment-related rather than speeding-related, allowing for more precise data-driven decision-making. The findings reveal that historically, over one-third of Arizona’s fatal crashes were coded as speeding-related. However, more than 53 percent of these speeding-coded fatal crashes also involved impaired drivers traveling below the posted speed limit. By correcting the interpretation to exclude behavioral conditions, the number of crashes coded as speeding-related (including both exceeding the limit and STFC) dropped from over 33 percent to approximately 11 percent of total fatalities. This adjustment removed significant portions of crashes attributed to DUI (53 percent), distraction (4 percent), and fatigue (3 percent) from the speeding category. Consequently, the percentage of fatal crashes coded as STFC decreased by more than one-third after the instruction changes were implemented. The significance of this work lies in its demonstration that precise data coding is essential for targeting effective countermeasures. By distinguishing between speeding and impairment, agencies can better allocate resources, applying enforcement strategies to impaired driving and engineering solutions to actual speeding problems. The paper concludes that updating crash forms provides greater consistency than training alone, as it reduces variability in officer interpretation. This approach allows for the identification of locations with genuine speeding issues, enabling the targeted application of measures like speed limit decals or automated enforcement, thereby improving overall traffic safety outcomes.

Key finding

Revising Arizona's crash-form coding to exclude impairment, distraction, and fatigue cut the share of fatal crashes coded speeding-related from over 33 percent to about 11 percent.

Methodology

other

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The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (7 acquisition events logged).

StageOutcomeToolModelPromptAttemptsCompleted
discover success rosap 2 2026-05-23
archive success 1 2026-05-23
extract success cached 2 2026-06-10
clean success 1 2026-06-01
chunk success 1 2026-06-01
embed success 1 2026-06-02
enrich success 1 2026-05-23
promote success 1 2026-05-23
summarize success llm qwen3.6-27b-prismaquant summ-v5 3 2026-06-10
tag success vector_similarity 19 2026-06-11
verify success 3 2026-06-10

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

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