Proactive assessment of road curve safety using floating car data: An exploratory study
DOI: 10.5604/01.3001.0013.5570
archive: archived pipeline: cataloged verified
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Summary
This exploratory study addresses the need for proactive road safety assessment, specifically focusing on horizontal curves where crash risks are elevated due to centripetal forces and driver workload. While traditional safety management relies on retrospective crash data, the authors aim to validate surrogate safety measures derived from Floating Car Data (FCD). The research specifically investigates the relationship between kinematic characteristics—acceleration and jerk—and crash occurrences on rural road curves, filling a gap in literature that previously focused primarily on speed or general driving behavior. The study utilized FCD collected from a fleet of company vehicles traveling on rural national roads in the Czech Republic. Data was recorded at a high frequency of 32 Hz to enable the calculation of jerk (the rate of change of acceleration). The researchers analyzed 53 curve-directions from 29 curves, deriving longitudinal and lateral acceleration and jerk values. To establish safety thresholds, the authors conducted a "risk cut-off" analysis, correlating kinematic indicators with annual crash rates. Subsequently, they performed a "risk rate" analysis, calculating the proportion of vehicle trips exceeding these thresholds. These risk rates were incorporated into generalized linear models (negative binomial error structure) alongside traditional variables such as traffic volume, curve length, and radius to predict crash frequency. The analysis identified specific cut-off values for hazardous situations: lateral acceleration of 0.3 g and longitudinal jerk of 0.1 g/s. When these thresholds were used to calculate risk rates, the resulting "combined model" demonstrated improved goodness-of-fit compared to a traditional model using only geometric and exposure variables. The combined model explained 79% of the systematic variation in crash frequency, compared to 70% for the traditional model, and showed a reduced overdispersion parameter. Although statistical significance levels were modest due to the small sample size, the regression coefficients indicated expected positive associations between the kinematic risk rates and crash frequency. The findings suggest that lateral acceleration and longitudinal jerk are influential surrogate measures for proactively evaluating curve safety. The study concludes that FCD can generate useful indicators for identifying safety-critical sites and monitoring the effectiveness of road safety treatments, such as signage or delineation. Potential applications include interim evaluations of curve improvements and in-vehicle monitoring systems that provide real-time feedback to drivers. The authors recommend larger-scale studies to strengthen the robustness of these results and expand the analysis to include additional road design parameters.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-20 |
| archive | success | canonical_url | — | — | 1 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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- Empirical Findings: crash risk outcomes, observational prevalence
- Methodological Resource: dataset resource