Factors Influencing Multi-vehicle Collisions Following Sudden Fatal Health Problems in Drivers

Kataoka, Hitomi; Hitosugi, Masahito; Takeda, Arisa; Takaso, Marin; Baba, Mineko; Nakamura, Mami · 2025 · Crossref

DOI: 10.7759/cureus.80438

archive: archived pipeline: cataloged verified

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Summary

This study investigates the kinematics and contributing factors of motor vehicle collisions (MVCs) resulting from sudden, fatal health problems in drivers. Motivated by the significant global burden of road traffic injuries and the increasing prevalence of older drivers with underlying health conditions, the research aims to provide data necessary for developing driver monitoring systems and pre-crash safety technologies. Specifically, the authors sought to understand vehicle behavior immediately after a driver’s incapacitation to identify strategies for minimizing multi-vehicle collisions and casualties. The researchers conducted a retrospective analysis of forensic autopsy records from two Japanese medical universities between 1998 and 2023. From an initial pool of 70 cases, they identified 68 drivers who experienced a sudden fatal health change while operating a four-wheeled vehicle and subsequently collided with an object. Data collected included driver demographics, vehicle type, collision velocity, road characteristics, and the vehicle’s trajectory relative to the direction of travel. Statistical analyses, including multivariable logistic regression, were performed to determine factors independently associated with collisions involving other vehicles versus single-vehicle collisions. The results indicated that heart disease was the predominant cause of death, accounting for 76% of cases, followed by aortic and cerebrovascular diseases. The mean age of drivers was 59 years, and the majority were male. Regarding collision dynamics, 37% of incidents occurred at speeds of 40 km/h or higher. Of the 68 collisions, 17 involved other vehicles, while 51 involved stationary objects such as poles, curbs, or trees. Crucially, the multivariable logistic regression analysis revealed that the vehicle’s direction of travel was a significant predictor of collision type. Moving forward and to the left (toward the roadside in left-hand traffic Japan) was significantly associated with avoiding collisions with other vehicles (odds ratio 0.026, p=0.007), compared to moving straight ahead. Conversely, moving forward and to the right (toward oncoming traffic) showed a trend toward higher risk, though it did not reach statistical significance in the final model. No significant differences were found regarding time of day, collision velocity, or driver consciousness levels between multi-vehicle and single-vehicle collision groups. The study concludes that pre-crash safety technologies should prioritize steering incapacitated vehicles toward the roadside rather than allowing them to continue straight or drift into oncoming traffic. The findings support the development of autonomous systems capable of detecting driver health abnormalities and executing evasive maneuvers to minimize harm. Additionally, the high incidence of heart disease and the potential for rapid rescue if drivers are located quickly underscore the need for integrated driver monitoring and automatic emergency notification systems. These insights are critical for enhancing road safety protocols and reducing fatalities associated with sudden driver incapacitation.

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StageOutcomeToolModelPromptAttemptsCompleted
discover success Crossref 1 2026-06-24
archive success canonical_url 1 2026-06-26
extract success cached 2 2026-06-26
clean success clean 1 2026-06-26
chunk success chunk 1 2026-06-26
embed success embed Qwen/Qwen3-Embedding-8B 1 2026-06-26
enrich success openalex 1 2026-06-26
promote success 1 2026-06-24
summarize success llm qwen3.6-27b-prismaquant summ-v5 1 2026-06-26
tag success vector_similarity 6 2026-06-26
verify success 1 2026-06-26

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

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