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Micro-Genetic algorithms in intelligent traffic signal control

机译:智能交通信号控制中的微遗传算法

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This paper presented a micro-GA based algorithm to optimize dynamical traffic signal control systems operating in oversaturated conditions. The objective of the control algorithm is to find, for a given control period, the near-optimal control trajectory (green splits an offsets) for a series of closely spaced traffic signals along an oversaturated arterial such that system throughput is maximized. The problem was solved using a micro-Genetic Algorithm (micro-GA). GAs were used because of their robustness, adaptive capabilites, and ability to overcome combinatorial explosions typical of highly dimensional problems like the one at hand. Despite the vast size of the solution set, the GA was able to converge to a near-optimal solution in very short time. The results show that the control algorithm provides efficient traffic control such that undesirable conditions such as queue build-up and spill-back are prevented. lntelligent and adaptive capabilities such as these would be of critical value in an intelligent transportation systems (ITS) environment, particularly during oversaturated conditions.
机译:本文提出了一种基于微GA的算法,用于优化在过饱和条件下运行的动态交通信号控制系统。控制算法的目标是在给定的控制周期内,针对沿过饱和动脉的一系列紧密间隔的交通信号找到最佳控制轨迹(绿色分割偏移量),以使系统吞吐量最大化。使用微型遗传算法(micro-GA)解决了该问题。使用GA的原因在于它们的坚固性,自适应功能以及克服诸如像手头这样的高维问题所特有的组合爆炸的能力。尽管解决方案集的规模很大,但GA能够在很短的时间内收敛到接近最优的解决方案。结果表明,该控制算法提供了有效的流量控制,从而避免了诸如队列建立和溢出等不良情况的发生。诸如此类的智能和自适应功能在智能运输系统(ITS)环境中,尤其是在过饱和条件下,将具有至关重要的价值。

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