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A Dynamic Traffic Signal Timing Model and Its Algorithm for Junction of Urban Road

机译:城市道路交叉口动态交通信号配时模型及其算法

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As an important part of Intelligent Transportation System, the scientific traffic signal timing of junction can improve the efficiency of urban transport. This paper presents a novel dynamic traffic signal timing model. According to the characteristics of the model, hybrid chaotic quantum evolutionary algorithm is employed to solve it. The proposed model has simple structure, and only requires traffic inflow speed and outflow speed are bounded functions with at most finite number of discontinuity points. The condition is very loose and better meets the requirements of the practical real-time and dynamic signal control of junction. To obtain the optimal solution of the model by hybrid chaotic quantum evolutionary algorithm, the model is converted to an easily solvable form. To simplify calculation, we give the expression of the partial derivative and change rate of the objective function such that the implementation of the algorithm only involves function assignments and arithmetic operations and thus avoids complex operations such as integral and differential. Simulation results show that the algorithm has less remain vehicles than Webster method, higher convergence rate and convergence speed than quantum evolutionary algorithm, genetic algorithms and particle swarm optimization.
机译:作为智能交通系统的重要组成部分,科学的路口交通信号定时可以提高城市交通效率。本文提出了一种新颖的动态交通信号时序模型。根据模型的特点,采用混合混沌量子进化算法对其进行求解。所提出的模型结构简单,只要求流量的流入和流出的速度是具有最多不连续点数量的有界函数。该条件非常宽松,可以更好地满足路口实际实时和动态信号控制的要求。为了通过混合混沌量子进化算法获得模型的最优解,将模型转换为易于求解的形式。为了简化计算,我们给出目标函数的偏导数和变化率的表达式,使得算法的实现仅涉及函数分配和算术运算,从而避免了诸如积分和微分之类的复杂运算。仿真结果表明,该算法比韦伯斯特算法具有更少的剩余载流子,比量子进化算法,遗传算法和粒子群优化算法具有更高的收敛速度和收敛速度。

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