Hazardous materials (hazmat) transportation accidents may cause severe casualties and environmental damage, highlighting the need for effective risk-mitigation strategies. In mixed traffic environments, hazmat vehicles share road resources with regular traffic, and the resulting congestion effects may further affect travel costs, traffic flow distribution, and transportation risk. This study proposes a speed-limit strategy for hazmat vehicles to reduce network transportation risk. A government–carrier bilevel optimization model was developed to characterize the decision-making relationship between regulatory authorities and transportation users. In the upper-level model, the regulatory authority determines the speed limits for hazmat vehicles on each link to minimize population-exposure-based network transportation risk. In the lower-level model, hazmat and regular traffic are incorporated into a multiclass user equilibrium framework, where the effects of hazmat speed limits on their travel costs and the congestion effects of aggregate traffic flow in the mixed traffic environment are incorporated into link travel costs. To address the computational challenges arising from complementarity constraints and nonlinear travel time functions, the bilevel model was reformulated as a mixed-integer linear programming model and solved using binary-variable linearization and special ordered sets of type 2 (SOS2)-based piecewise linearization. Numerical experiments on the Tilburg and Sioux Falls networks showed that reducing speed limits generally decreases the modeled network transportation risk, with maximum reductions of 35.12% and 7.91%, respectively, while the travel delay of hazmat vehicles correspondingly increases, with maximum increases of 19.71% and 11.15%, respectively. The proposed framework provides decision support for transportation authorities in designing network-level speed-limit strategies while accounting for congestion effects in mixed traffic environments and their implications for hazmat transportation risk.
Citation: Guanxiang Zhang, Haidong Huang. Risk optimization of hazardous materials transportation through differentiated speed limit strategies in mixed traffic networks[J]. Journal of Industrial and Management Optimization, 2026, 22(11): 5625-5650. doi: 10.3934/jimo.2026191
Hazardous materials (hazmat) transportation accidents may cause severe casualties and environmental damage, highlighting the need for effective risk-mitigation strategies. In mixed traffic environments, hazmat vehicles share road resources with regular traffic, and the resulting congestion effects may further affect travel costs, traffic flow distribution, and transportation risk. This study proposes a speed-limit strategy for hazmat vehicles to reduce network transportation risk. A government–carrier bilevel optimization model was developed to characterize the decision-making relationship between regulatory authorities and transportation users. In the upper-level model, the regulatory authority determines the speed limits for hazmat vehicles on each link to minimize population-exposure-based network transportation risk. In the lower-level model, hazmat and regular traffic are incorporated into a multiclass user equilibrium framework, where the effects of hazmat speed limits on their travel costs and the congestion effects of aggregate traffic flow in the mixed traffic environment are incorporated into link travel costs. To address the computational challenges arising from complementarity constraints and nonlinear travel time functions, the bilevel model was reformulated as a mixed-integer linear programming model and solved using binary-variable linearization and special ordered sets of type 2 (SOS2)-based piecewise linearization. Numerical experiments on the Tilburg and Sioux Falls networks showed that reducing speed limits generally decreases the modeled network transportation risk, with maximum reductions of 35.12% and 7.91%, respectively, while the travel delay of hazmat vehicles correspondingly increases, with maximum increases of 19.71% and 11.15%, respectively. The proposed framework provides decision support for transportation authorities in designing network-level speed-limit strategies while accounting for congestion effects in mixed traffic environments and their implications for hazmat transportation risk.
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Guanxiang Zhang, Haidong Huang. Risk optimization of hazardous materials transportation through differentiated speed limit strategies in mixed traffic networks[J]. Journal of Industrial and Management Optimization, 2026, 22(11): 5625-5650. doi: 10.3934/jimo.2026191
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