Journal of System Simulation ›› 2024, Vol. 36 ›› Issue (5): 1165-1178.doi: 10.16182/j.issn1004731x.joss.23-0090

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Optimization of Highway Emergency Lane Control Based on Kriging Genetic Algorithm

Tang Jinjun(), Hu Lipeng, Li Mingyang, Zhang Xuan   

  1. School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
  • Received:2023-02-06 Revised:2023-05-08 Online:2024-05-15 Published:2024-05-21


To address the issue of how to effectively improve the highway operational efficiency and reduce the safety risks under different traffic flow conditions, this study proposed a genetic algorithm based on Kriging agent model is proposed to optimize the emergency lane control strategy. A mathematical optimization model is designed by combining the spatial and temporal characteristics of the emergency lane opening strategy. By introducing Kriging agent model, combining the genetic algorithm to build the optimization framework, and using simulation software to obtain data to train the agent model, the problem of minimizing the total travel time and the total exposed time-to-collision with both time and space constraints is solved. The change frequency of the emergency lane control at time and space dimension is constrained. The effect of the change of weights for efficiency and safety indicators in the objective function on the optimization results. Comparison in experiments show that the proposed optimization method reduces the total travel time of the road network by 14.9% and the total time exposed time-to-collision by 44.2%.

Key words: smart highway, emergency lane, Kriging agent model, genetic algorithm, space-time constraints, simulation of urban mobility(SUMO)

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