系统仿真学报 ›› 2015, Vol. 27 ›› Issue (6): 1348-1356.doi: 10.16182/j.cnki.joss.2015.06.028

• 信息、控制、决策与仿真 • 上一篇    下一篇

一种高效的实时交通信号灯控制算法

杨忠程1,2, 叶晨1,2, 杨振宇1,2   

  1. 1.同济大学电于与信息工程学院,上海 201804;
    2.同济大学嵌入式系统与服务计算教育部重点实验室,上海 201804
  • 收稿日期:2014-06-05 修回日期:2014-12-09 出版日期:2015-06-08 发布日期:2021-01-15
  • 作者简介:杨忠程(1989-),男,浙江省温州市,硕士生,研究方向为智能交通; 叶晨(1980-),男,安徽省天长市,博士生,讲师,研究方向为嵌入式计算、智能交通、无线网络; 杨振宇(1988-),男,安徽省淮北市,博士生,研究方向为智能交通。
  • 基金资助:
    科技部国际合作专项(2012DFG11580)

Efficient Real-time Traffic Signal Control Algorithm

Yang Zhongcheng1,2, Ye Chen1,2, Yang Zhenyu1,2   

  1. 1. Department of Computer Science and Technology, Tongji University, Shanghai 201804, China;
    2. The Key Laboratory of Embedded System and Service Computing (Ministry of Education), Tongji University, Shanghai 201804, China
  • Received:2014-06-05 Revised:2014-12-09 Online:2015-06-08 Published:2021-01-15

摘要: 针对交通信号灯实时控制问题,设计了一种以最小化车辆等待时间为目标的数学模型,并给出了一种能求解该模型最优解的启发式搜索算法。仿真结果显示启发式搜索算法存在求解时间长,求解效率不稳定等问题。因此在原算法基础,上加入了多阶段决策优化方法,并且在各个阶段中采用了限时搜索,使得算法能在固定时间内得到结果,保证了算法的稳定性和实时性。通过实际数据仿真显示,优化后的算法对比固定周期算法减少了车辆的等待时间;对比原始的启发式搜索算法,提高了求解效率,满足了实时控制的要求。

关键词: 实时交通信号灯控制, 启发式搜索, 多阶段决策优化, 限时搜索

Abstract: For real time taffic signal contol isus, a mathematical model was proposed to minimize the waiting ime, meanwhile a huristi search aigorihm was given to sove the optinal sluton Simulatin Tresuts show that the hcurisi scarceh algorim sufrfs fom being couataoalal complx and umstable, therefore, a multi sage decisin optimization algorihm is added, and the serehes adopt in all stages subject to a time limit, which ensures a stable and real-time algorithm, and also a soution in fixed time. Simulation resuts based on actal tafic data show that the waiting time can be reduced in comparison with that of tbe fxc-ine perioic contol policy, the compuation time can be saved in comparison with that of the original heuristic search algorithm and it can be apied to realtim tafic control.

Key words: Treal- time tafic signal control, heuristic search, multi- stage decision optimizatin, limited

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