Identification of Specific Problems and Countermeasures Targets for Reducing Alcohol Related Casualties [1975]

Perchonok, Kenneth · 1975 · ROSA P / United States. Department of Transportation. National Highway Traffic Safety Administration

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Summary

This 1975 report by Kenneth Perchonok, prepared for the National Highway Traffic Safety Administration, addresses the need for a detailed empirical profile of drinking drivers to inform targeted countermeasures. While previous research relied heavily on laboratory performance studies or broad statistical accident rates, this study aimed to delineate specific accident characteristics, situational contexts, and driver behaviors associated with alcohol-related crashes. The objective was to identify the specific problems of drinking drivers compared to nondrinkers to determine effective remedial targets. The methodology involved analyzing police reports of accidents in an eight-county area of Western New York. The study focused on "culpable" driver/vehicle units—those responsible for initiating the accident sequence. Researchers compared drinking drivers (categorized as those cited for Driving While Intoxicated [DWI] or those reported as drinking but not cited [HBD]) against nondrinking drivers. Analyses covered accident configurations, critical events, situational variables (such as time of day, road type, and weather), and driver histories. Additionally, telephone interviews were conducted with a sample of culpable drivers to verify police reports and assess driver familiarity with accident locations. Key findings revealed that drinking drivers exhibited extremely high culpability rates, ranging from 90 to 95 percent. They were disproportionately male and, while young drivers (19–20) were highly represented, the largest absolute number of drinking accidents involved drivers over 21. Drinking drivers were significantly more likely to be involved in "Class R" accidents, where the vehicle leaves its path laterally to strike a stationary object or road edge; these accounted for 42 percent of drinking accidents versus 18 percent for nondrinkers. Drinking drivers also showed a propensity for accidents in low-demand situations, such as nighttime driving on unlighted, rural, two-lane roads with dry surfaces. In contrast, nondrinkers benefited from these low-conflict conditions, whereas drinkers did not. Furthermore, drivers with previous alcohol convictions had a much higher incidence of drinking in subsequent accidents (36 percent) and higher culpability rates than those without such history. The study concludes that the primary countermeasure targets should address Class R and rear-end accidents, particularly involving older males at night. Because drinking drivers often fail in simple lane maintenance tasks rather than complex maneuvers, the report suggests that simplifying the driving environment may be counterproductive. Instead, it proposes active lane delineation techniques to warn drivers of out-of-lane moves and active upstream warnings at intersections to prevent rear-end collisions. The findings also imply that mood effects, rather than pure physiological impairment, may drive risky behavior, as cited DWI drivers often exhibited more cautious patterns than uncited HBD drivers. Consequently, the report recommends increasing the perceived risk of drinking and driving through enhanced punitive measures and ignition interlock systems for convicted offenders.

Key finding

Culpable drinking drivers exhibited extremely high culpability rates and were disproportionately involved in class R accidents, rear-end collisions, and lane departure incidents in low-demand situations compared to non-drinking drivers.

Methodology

dataset

Provenance

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

Topics

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• sex gender
• incidence prevalence
• alcohol
• pre crash contributing factors
• demographic disparities
• human error taxonomy

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