2026-10-14T00:30:32Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33866358 2026-09-16T17:38:15Z category_21 category_272 category_873 category_45 category_734 category_61 category_64 portal_5 item_type_3 month_year_09_2026

<p>Descriptive statistics of in-depth crash data.</p> Turki A. Alamoudi (24998718) Saif A. Alarifi (24998721) Biotechnology Environmental Sciences not elsewhere classified Chemical Sciences not elsewhere classified Sociology Biological Sciences not elsewhere classified Developmental Biology Cancer integrating statistical analysis identify key predictors findings provide robust descriptive statistics revealed approximately 45 %, 2020 &# 8211 054 ), underscoring 001 ), indicating ), embankment gradient fully compacted embankments fatality crash data reduced rollover probability higher speed limits 017 per km fidelity vehicle simulations zone characteristics influence soil compaction protocols 3 &# 8211 based roadside clear soil compaction 10 ), roadside clear steep embankments clear zone speed profiles posted speed 140 km 100 km vehicle type vehicle stability vehicle classes fatality crashes zone width zone design varied clear emphasizing clear rollover crashes study investigates steep slope rural highways odds ratio gentler grades enhance safety destabilizing effect depth investigations depth dataset complementary finite based guidance 59 fatalities <div><p>Saudi Arabia’s rural highway network experiences a high number of severe run-off-road and rollover crashes, yet evidence-based, locally validated roadside clear-zone design guidance remains limited. This study investigates how roadside clear-zone characteristics influence the occurrence and severity of these crashes by integrating statistical analysis of in-depth investigations of multi-fatality crash data with high-fidelity vehicle simulations. An in-depth dataset of 127 multi-fatality crashes (2020–2022) from the National Road Safety Centre was analyzed using binary logistic regression to identify key predictors of run-off-road severity. The final model retained three significant variables: Vehicle Type (odds ratio OR = 0.56 per class increase, p < 0.001), indicating that heavier vehicle categories diminish rollover risk; Posted Speed (OR = 1.017 per km/h increase, p = 0.032), reflecting elevated crash likelihood at higher speed limits; and Steep Slope (V:H ≥ 1:4) (OR = 2.73, p = 0.054), underscoring the destabilizing effect of steep embankments on vehicle stability. Descriptive statistics revealed an average of 3.59 fatalities and 2.80 injuries per crash, with single-vehicle incidents comprising 78% of the sample. Complementary finite-element simulations using AnalyzerPro examined sixteen scenarios that varied clear-zone width (3–7 m), embankment gradient (1:2.5 vs. 1:10), and soil compaction at speeds of 100 km/h and 140 km/h. Widening the clear zone from 3 m to 7 m reduced rollover probability by approximately 45%, while fully compacted embankments and slopes consistently prevented rollovers across all vehicle classes and speed profiles. Steeper slopes markedly increased rollover propensity relative to gentler grades. These findings provide robust, evidence-based guidance for updating roadside design standards—emphasizing clear-zone widening, soil compaction protocols, and slope moderation—to enhance safety on Saudi Arabia’s rural road network.</p></div> 2026-09-16T17:38:00Z Dataset Dataset 10.1371/journal.pone.0357284.t003 https://figshare.com/articles/dataset/_p_Descriptive_statistics_of_in-depth_crash_data_p_/33866358 CC BY 4.0