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基于FPGA的遗传算法在交通控制中的应用

2015-08-14张丽霞唐泽

现代电子技术 2015年15期

张丽霞 唐泽

摘 要: 智能交通灯是智能交通系统的重要组成部分,它能有效增加道路的通行能力,改善交通状况。采用道路各相位在一个周期内滞留的车辆数作为识别判据,将遗传算法应用到交通灯控制中,并且利用FPGA的并行计算优势,实现算法的硬件化,减少算法的运行时间。交通灯整体的实现基于Nios Ⅱ嵌入式处理器。实验结果表明,交通灯能根据车流量实现智能配时,基于FPGA的遗传算法比基于传统计算机的遗传算法在运行速度上有很大的提高,使得一些大规模、复杂的问题有了解决的可能性。

关键词: 智能交通灯; 现场可编程门阵列; 遗传算法; Nios Ⅱ

中图分类号: TN965+.71?34; TP332.3 文献标识码: A 文章编号: 1004?373X(2015)15?0153?05

Application of FPGA?based genetic algorithm in traffic control

ZHANG Lixia1, TANG Ze2

(1. Department of Information Engineering, Sichuan Vocational and Technical College of Communications, Chengdu 611130, China;

2. College of Information Science and Technology, Southwest Jiaotong University, Chengdu 610000, China)

Abstract: Intelligent traffic light is an important part in intelligent transportation system, it can increase road traffic capacity and improve traffic situation effectively. Taking the vehicle number of each direction detained in a period as recognition criterion, genetic algorithm (GA) is applied in traffic lights control system. The advantage of FPGA parallel computing is applied to achieving the algorithm′s hardware implementation, which can reduce running time of the algorithm. The implementation of the integral traffic light system is based on Nios II embedded processor. The experimental results show that traffic light system can realize intelligent timing according to traffic flow. FPGA?based GA has great improvement in operating speed in comparison with the GA which is based on traditional computer. It makes the problems of large scale and complex have solved possibility.

Keywords: intelligent traffic light; FPGA; genetic algorithm; Nios Ⅱ

0 引 言

随着机动车数量的快速增长,道路的拥挤程度也随之增加。单一的交通信号灯控制方法往往难以适应复杂多变的交通流,造成空等、浪费时间等现象,影响道路的通行能力;所以智能交通灯的出现势在必行[1]。本文采用在道路叉口各相位单位时间内到达和离开车辆数的差来作为识别判据,结合道路饱和度,提出感应控制和基于遗传算法的自适应控制。遗传算法广泛应用于智能控制中,但大部分的应用都采用具有冯诺依曼或哈弗结构的计算机去实现,因为这两种结构是串行计算的原因,遗传算法在运行时间上往往不是很理想,当面临一些大规模、复杂问题时,往往导致计算无法实现[2]。而现场可编程门阵列(Field Programmable Gate Array,FPGA)的出现及它的并行计算优势,使得基于FPGA的遗传算法在运行时间上会有数量级的提高[3]。……

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