Traffic Signal Timing Optimization Based On Multi-Strategy Improved Harris Hawks Algorithms

With urbanization accelerating in China,traffic congestion is becoming more and more serious.Traffic congestion occurs at the intersections of the main road sections.Therefore,the design of optimizing intersections is essential to improving road traffic capacity.A practical solution is to allocate signal lights at intersections rationally.Intelligent algorithm is commonly used to solve traffic signal timing optimization.Harris Hawks algorithm is a new swarm intelligence algorithm,but it also has some problems such as premature convergence and limited diversity,so this paper studies and improves the shortcomings of Harris Hawks algorithm,and applies it to solving the traffic signal timing problem.The specific research content is as follows:(1)A Harris Hawks Optimization Algorithm(HHOG)is proposed.In HHOG,chaotic mapping is added to improve the global search ability of the algorithm.It utilizes the Cauchy function to control the Levy flight step size to achieve a smooth transition,using the Gaussian random walk strategy to improve the search accuracy and convergence speed.HHOG and five other typical optimization algorithms are tested on 16 benchmark functions,proving the effectiveness of the methods.(2)An Improved Harris Hawks Optimization(IHHO)is proposed,In IHHO,elite opposition-based learning strategy is added to enhance the diversity of population in search space,and Golden Sine Algorithm is integrated to improve the efficiency and global search ability of the algorithm.It uses a nonlinear control parameter to adjust the exploration and development behavior of the algorithm,avoiding the probability of the local optimal solution.Through the optimization experiment of the test function,the improvement of IHHO in search accuracy and convergence speed is verified.(3)From the perspective of vehicle traffic efficiency and environmental protection,this thesis takes traffic capacity,vehicle delay,exhaust emission,and the number of stops as optimization indicators,using the effective green light time and signal cycle time of intersections as constraints to establish a traffic signal timing model.Taking a typical intersection as an example,using two improved Harris Hawks algorithms to solve the traffic signal timing model,respectively,obtaining the signal timing scheme with the highest comprehensive benefit.It optimizes the traffic capacity,vehicle delay,exhaust emission,and parking times.The experimental results are compared with the original scheme and the improved Webster method to verify the effectiveness of the model and the feasibility of the Harris Hawks algorithm.