Fatal Wrong-Way Crashes on Divided Highways, United States, 2014-2023
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Summary
This study analyzes the prevalence and risk factors associated with fatal wrong-way crashes on divided highways in the United States from 2014 to 2023. Motivated by the severe safety outcomes of these relatively rare events and their growing frequency, the research updates previous findings from the AAA Foundation for Traffic Safety. The analysis aims to identify specific driver, vehicle, and environmental characteristics that increase the likelihood of a driver entering a highway in the wrong direction, thereby informing targeted countermeasures. The researchers utilized data from the Fatality Analysis Reporting System (FARS), identifying 4,164 fatal wrong-way crashes resulting in 5,730 fatalities. Cases were defined as crashes where the driver was reported driving the wrong way on one-way or divided roads, excluding crossover crashes. To assess risk factors, the study employed two complementary statistical modeling approaches: conditional logistic regression comparing wrong-way drivers to right-way drivers involved in the same crash (matched analysis), and ordinary logistic regression comparing wrong-way drivers to all non-contributing right-way drivers in fatal crashes during the same period (non-matched analysis). Missing blood alcohol concentration (BAC) values were addressed using a custom multiple imputation model to avoid bias. The results indicate that fatal wrong-way crashes approximately doubled over the decade, rising from 278 incidents in 2014 to 520 in 2023, increasing their share of total fatal crashes on divided highways from 3.4% to 4.6%. Alcohol impairment emerged as the most significant risk factor; nearly 70% of wrong-way drivers had a BAC above the legal limit, with drivers having a BAC greater than 0.12 g/dL exhibiting over 80 times higher odds of being the wrong-way driver compared to sober drivers. Other confirmed risk factors included older age (drivers aged 70+ had significantly elevated odds), invalid or missing licenses, and driving older vehicles. The study also identified new risk factors: crashes were more likely in rural areas, during darkness or dawn/dusk, and among drivers far from their home zip codes. Conversely, the presence of passengers and driving large trucks or buses were protective factors, significantly reducing the odds of wrong-way involvement. The findings underscore that while wrong-way crashes remain a small fraction of total fatalities, their disproportionate increase highlights a critical safety concern. The identification of alcohol impairment, older age, and unfamiliarity with the environment (proxied by distance from home) as key drivers suggests that countermeasures should focus on preventing impaired driving, enhancing signage and detection systems in rural and low-light conditions, and improving driver education for complex interchanges. The study supports the implementation of integrated systems combining infrastructure improvements, such as enhanced signage and pavement markings, with active detection technologies to alert drivers and emergency responders.
Key finding
Alcohol impairment, advanced age, invalid licensing, and older vehicles are primary risk factors for fatal wrong-way crashes, with additional elevated risks observed in rural settings, low-light conditions, and among drivers operating vehicles registered to others or located far from their home.
Methodology
dataset
Sample size: 4176
Provenance
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_aaa_foundation on 2026-05-23 (5 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | aaa_foundation | — | — | 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 | skipped | — | — | — | 3 | 2026-07-02 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 18 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
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.
- pre crash contributing factors
- incidence prevalence
- demographic disparities
- induced exposure
- rail grade crossings
- urban rural setting
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