Dynamic Optimization of Highway Emergency Lane Activation Using Kriging Surrogate Modeling and NSGA-II

Yi Fei, Yanan Wang and Qiuyan Zhang ()
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Yi Fei: College of Applied Mathematics, Chengdu University of Information Technology, Chengdu 610225, China
Yanan Wang: College of Applied Mathematics, Chengdu University of Information Technology, Chengdu 610225, China
Qiuyan Zhang: College of Applied Mathematics, Chengdu University of Information Technology, Chengdu 610225, China

Sustainability, 2025, vol. 17, issue 18, 1-31

Abstract: Highway congestion is a persistent issue, and dynamically activating emergency lanes offers a promising mitigation strategy. However, traditional fixed-time or single-threshold methods often fail to balance traffic efficiency and safety. This paper introduces a dynamic optimization framework that integrates a Kriging surrogate model with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to identify optimal activation strategies. By simultaneously minimizing total travel time (efficiency) and the duration vehicles spend in unsafe proximity (safety), our method generates a set of Pareto-optimal solutions. We calibrated and validated the model using real-world highway data. The results are compelling: the optimized compromise strategy reduced total travel time by 20.5% compared to having no activation, while keeping safety risks within an acceptable range. The use of a Kriging surrogate model sped up the optimization process by approximately 20 times compared to direct simulation, achieving a prediction accuracy of 97.8%. The optimal strategies characteristically involve opening the emergency lane at the downstream bottleneck during peak congestion and closing it promptly as traffic eases. This research provides a robust, efficient, and practical decision-support tool for intelligent traffic management, offering a clear pathway to safer and less congested highways.

Keywords: dynamic emergency lane activation; bi-objective optimization; kriging surrogate model; genetic algorithm; cell transmission model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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