Abstract
Intersection traffic lights are a basic means of ensuring the normal operation of road traffic. A good signal timing scheme is essential for improving traffic congestion. To obtain the signal timing scheme of the designated intersection, the method proposed in this article is based on a modified Webster function. The method uses the signal cycle and proportion of green light duration as independent variables to establish the corresponding intersection vehicle delay function. This function is converted from a multiobjective optimization to a single-objective optimization formulation; a modified genetic algorithm is then used to find the optimal solution to this function. The experimental results show that the timing scheme optimized by the improved genetic algorithm can reduce the intersection delay by nearly 15.64%. The proposed traffic signal timing based on the modified Webster function will be of value as an important reference for the optimization of traffic lights at urban intersections.
Highlights
Traffic simulations to confirm the optimization of signal light timing exist in the literature
Using the traditional Webster delay function, Liuyi et al [17] constructed a traffic simulation model and evaluated it using a VISSIM simulation that includes delay, average parking time, queue length, and vehicle parking times. e simulation results show that the delay of the optimized intersection is reduced by 22.3% to 21.29 s, the parking time is reduced by 24.2%, and the average queue length and average parking time are improved
To calculate the signal light timing according to the actual road conditions, the following approach is taken in this study: (1) to obtain a target optimization model with high precision, the traditional Webster function is fit to the point sample function and (2) a modified genetic algorithm is used to solve for the optimal value of the function with constraints, and constraints of the genetic algorithm are used to initialize the chromosome parent to realize the optimal value solving the process of the function. e change in the total delay at the intersection before and after optimization is compared to evaluate the performance of the algorithm
Summary
Huizhen Zhang ,1,2 Hongtao Yuan, Youqing Chen ,1 Wenlong Yu, Cheng Wang, Jing Wang, and Yueer Gao 3. To calculate the signal light timing according to the actual road conditions, the following approach is taken in this study: (1) to obtain a target optimization model with high precision, the traditional Webster function is fit to the point sample function and (2) a modified genetic algorithm is used to solve for the optimal value of the function with constraints, and constraints of the genetic algorithm are used to initialize the chromosome parent to realize the optimal value solving the process of the function. From an engineering perspective, to improve the efficiency of the solution, the multiobjective optimization function must be transformed into a single-objective optimization function In response to this problem, the approach in this paper multiplies the average delay of the vehicles in each direction fnew(C(t,t+Δ t), λ1, λ2, . Boundary, chromosome length, total number of iterations, selection probability, crossover probability, mutation probability
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