Swarm Intelligence Based Traffic Control System

Bindu Varshini Kosanam, Abhinay Kukkadapu
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Abstract

Traffic congestion is one of the major problems in many of metro cities all over the world today. It affects daily life in many aspects such as improper time management, stress, frustration which leads to reckless driving. Average time to reach destination is decided by travel speed which is directly proportional to traffic congestion and also the wait time at each and every traffic signal. In this paper a novel Swarm Intelligence based Traffic Control System (SITS) inspired from nature mimicking (Particle Swarm Optimization) is discussed. This State of the art SITS with Six Degrees of Separation approach to traffic congestion is applying swarm intelligence to traffic lights to avoid waiting of vehicles at red light decreasing wait time and congestion. Here cars will not take random paths or will not take dynamic routes. Six degrees of separation will be employed at each node (traffic signal) to limit computational power and to improve efficiency.
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基于群体智能的交通控制系统
交通拥堵是当今世界许多地铁城市面临的主要问题之一。它影响日常生活的许多方面,如时间管理不当,压力,沮丧,导致鲁莽驾驶。到达目的地的平均时间由旅行速度决定,而旅行速度与交通拥堵和每个交通信号的等待时间成正比。本文讨论了一种受自然模拟(粒子群优化)启发的基于群体智能的新型交通控制系统。这种最先进的六度分离交通拥堵方法是将群体智能应用于交通信号灯,以避免车辆在红灯前等待,减少等待时间和拥堵。在这里,汽车不会走随机路径,也不会走动态路线。每个节点(交通信号)将采用六度分隔,以限制计算能力并提高效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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