Research on virtual emergency lane optimization and control strategy based on VISSIM expressway

Following highway accidents, obstructed rescue access and delayed information dissemination severely limit emergency response efficiency. This study proposes a Virtual Emergency Lane (VEL) strategy that dynamically reallocates lane usage based on real-time traffic data to facilitate rescue vehicle passage under congestion. Using the VISSIM microscopic simulation platform, multiple accident scenarios-varying in lane closure numbers and volume-to-capacity (v/C) ratios-were modeled to evaluate VEL performance. A regression-based predictive model quantified optimization benefits across traffic loads and revealed a performance peak with increasing demand. Results show that VEL significantly reduces travel time, queue length, stop frequency, and vehicle delay. Optimal performance occurs at v/C ratios of 0.9, 0.75, and 0.35 for single-, double-, and triple-lane closures, respectively. The findings validate VEL’s effectiveness and adaptability in various congestion scenarios, offering theoretical support and practical insight for intelligent emergency lane control strategies in highway incident management.