Performance Analysis of Active Prevention and Control Strategy for Driving Risk Before, On, and After Foggy Bridges Considering Crash and Noncrash Conditions

As critical infrastructure, bridges present heightened driving risks, particularly in foggy environments. To alleviate driving risks on foggy bridges, we propose an active prevention and control (APC) strategy combining risk warning, variable speed limit, and visual guidance. This study aimed to comprehensively quantify a driver’s performance in reducing driving risks with the APC strategy and facilitate the strategy’s application to enhance traffic safety. A driving simulation experiment was conducted on the E’dong Yangtze River Bridge, with a visibility of 100 m, using Unity + Logitech G29. Two schemes were designed comparing traditional traffic facilities with the APC strategy. The leading vehicle’s sudden stop simulated emergency avoidance. A human-factor-oriented multidimensional evaluation framework was established considering crash and noncrash conditions with three-phase metrics to quantify performance: before the bridge, the speed decrease rate (SDR) reflects advance speed regulation; on the bridge, the crash avoidance rate (CAR) and risk reduction rates (RRRs) reflect crash avoidance and risk reductions; after the bridge, the speed recovery rate (SRR) reflects driving state recovery. Results demonstrate the APC strategy regulates the speed step-by-step with increasing SDR, particularly 200–100 m before the bridge, which is conducive to avoiding the risk in advance. On the bridge, this strategy can avoid rear-end collisions with 100% CAR. For noncrashed drivers, all RRRs surpass 0, indicating that the APC strategy improves driving smoothness, drivers’ perception control (the highest improvement with 191.88% RRR), and psychological comfort, which can reduce potential crash risks in multiple aspects. The SRR reaches 47.77%, facilitating quicker driving state recovery after the bridge. This study demonstrates the APC strategy’s superiority over traditional measures through quantifiable and multidimensional human-factor metrics. The findings provide actionable insights for implementing the strategy to enhance safety and comfort on bridges and other frequently foggy roads.