Fuzzy Evaluation of Driving Safety at Tunnel Portals of Mountain Highways Based on Improved Rough Set Theory

Driving safety at tunnel portals on mountain expressways is affected by multiple factors, including driver behavior, traffic conditions, tunnel environment, and meteorological conditions. The combined effects of these factors introduce uncertainty and fuzziness into the assessment process. To address the limitations of the existing studies, which often focus on single risk factors or rely on subjective weighting methods, this study proposes an improved rough-set-based fuzzy comprehensive evaluation method incorporating the principle of minimum relative entropy. By integrating accident causation analysis, relevant standards and literature, and field investigations, a driving safety assessment indicator system for tunnel portals on mountain expressways is constructed. Attribute importance information derived from algebraic rough set theory and conditional information entropy rough set theory is first integrated. The principle of minimum relative entropy is then applied to determine the comprehensive indicator weights. Continuous and discrete indicators are then processed using membership functions and driving safety probability analysis, respectively, to establish a fuzzy comprehensive evaluation model. The results show that environmental factors and driver factors have substantial effects on driving safety at tunnel portals, with pavement icing, distracted driving, friction coefficient, and snowfall identified as the main influencing indicators. Validation using 15 tunnel portal cases on mountain expressways in Shanxi Province shows an agreement rate of 86.67% between the safety grades obtained using the proposed model and the actual accident grades. The findings provide a quantitative basis for safety risk identification, grade determination, and the operational management and control of tunnel portals on mountain expressways.