Severity analysis of head-on crashes on curves in mountainous terrain based on higher-order factor interactions:...

The study addressed the multifaceted nature of severe curve-based head-on crashes by identifying hidden high-risk scenarios/combinations, stemming from higher-order interaction between driver, crash, environmental, traffic and roadway characteristics along with spatial relationship indicators.

Association rule mining (ARM), due to its greater flexibility in handling and quantifying interactions than conventional models, was used to extract the high-risk scenarios/combinations from 533 curve-based head-on crashes in the mountainous state of Himachal Pradesh, India. Higher-order interactions were manifested through 3 and 4-factor interactions after fixing severity as the consequent. A minimum support, confidence/severity-rate, and lift of 2%, 50%, and 1.3, respectively, were established for extracting the initial rule space. From this space, based on an absolute raw support, "key rules" with raw support >25 and "exceptions" with that under 25 but with lift ≥ 1.9, were further extracted to prioritize significant associations. These were then integrated after eliminating redundant rules and the final rule set constituted 20 key rules and 4 exceptions. The stability and generalizability of the rules were validated through Fisher's exact test and stratified bootstrap sampling-based stability analysis.

Aggressive driving was a key trigger of many high-risk scenarios. Ineffective/inadequate risk communication and visibility restricted by narrow mountainsides (<1 m) increased the collision susceptibility on medium speed limit curves (30-50 kmph) by 1.6 times. Middle-aged heavy vehicle operators emerged as a vulnerable group on sections characterized opposing sequences/reverse curves, pavement width < 7 m and insufficient valley side clearance/buffer (<2.5 m). Severe collisions were 1.35 times more likely on longer curves (>90 m) with narrow mountainsides. Opposing sequences emerged as a significant hotspot of severe head-on crashes especially under conditions involving inadequate mountainside visibility (<1.5 m) and insufficient valley side buffer (<2.5 m). An important finding of the present study is that a relatively sharper curve in proximity (<240 m) increased the risk of a severe crash on a given subject curve. Specifically, very sharp curves (radius < 40m, length: 30-60 m) in succession emerged as one of the riskiest scenarios, doubling the collision risk. Collision risk increased significantly (1.986 times) with longer preceding curves, indicating potential hotspots.

Curve-based head-on crashes exhibited increased severity and produced multiple hotspots under specific combinations/scenarios involving aggressive driver behavior, mountain side visibility constraints, insufficient valley side buffer, vehicle-specific dynamics and inadequate pavement width. The associated risks were particularly exacerbated on closely-spaced curve sequences featuring sharper or longer approach curves and opposing orientations. The consistent involvement of spatial relationship indicators in multiple high-risk scenarios, advocates shift toward a system-based curve safety assessment, especially in mountainous areas. The identified high-risk scenarios/locations/configurations facilitate comprehensive safety profiling based on factor combinations instead of individual features, for designing multiple targeted interventions.