Analysis and Control of Intelligent Traffic Signal System Based on Adaptive Fuzzy Neural. Network

被引：0
|
作者：
Dong, Changqing [1 ]
Yang, Kaixin [2 ]
Guo, Jinwei [2 ]
Chen, Xiaowei [2 ]
Dong, Haibo [2 ]
Bai, Yunlong [2 ]
机构：
[1] Tianjin Univ, Coll Management & Econ, Tianjin, Peoples R China
[2] China Automot Technol & Res Ctr Co Ltd, Automot Data Ctr, Tianjin, Peoples R China
来源：
2019 5TH INTERNATIONAL CONFERENCE ON TRANSPORTATION INFORMATION AND SAFETY (ICTIS 2019) | 2019年
关键词：
Intelligent transport system; V2X; Traffic signal control; Adaptive fuzzy neural network;
D O I：
暂无
中图分类号：
U [交通运输];
学科分类号：
08 ; 0823 ;
摘要：
The paper proposes an intelligent traffic signal control system based on AFNN (Adaptive Fuzzy Neural Network) algorithm, which can adjust the signal cycle and green split to improve traffic efficiency. First, based on V2X (Vehicle to X) intelligent networking technology, the numbers of waiting vehicles at traffic light intersections are real-timely detected. Then, an AFNN algorithm is used to get the knowledge of experience and online self-adjustment is followed according to traffic state to optimize light signal control scheme. Finally, the validity and rationality of the system are verified by the system simulation model. The results show that with the help of the adaptive control system, the average delay time was reduced by 8.45%, and the average fuel economy increased by 24.04%.
引用
收藏
页码：1352 / 1357
页数：6
相关论文
共 50 条
  • [21] Intelligent control of the grinding and classification system based on fuzzy RBF neural network
    Wang, Yun-Feng
    Li, Zhan-Ming
    Yuan, Zhan-Ting
    Wan, Wei-Han
    Chongqing Daxue Xuebao/Journal of Chongqing University, 2010, 33 (03): : 124 - 128
  • [22] An intelligent traffic light control based on extension neural network
    Chao, Kuei-Hsiang
    Lee, Ren-Hao
    Wang, Meng-Hui
    KNOWLEDGE - BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS, 2008, 5177 : 17 - 24
  • [23] An Adaptive Fuzzy Neural Network for Traffic Prediction
    Bucur, L.
    Florea, A.
    Petrescu, B. S.
    18TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, 2010, : 1092 - 1096
  • [24] Adaptive Dynamic Neuro-fuzzy System for Traffic Signal Control
    Li, Tao
    Zhao, Dongbin
    Yi, Jianqiang
    2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 1840 - 1846
  • [25] Model predictive control of nonlinear system based on adaptive fuzzy neural network
    Zhou H.
    Zhang Y.
    Bai X.
    Liu B.
    Zhao H.
    Huagong Xuebao/CIESC Journal, 2020, 71 (07): : 3201 - 3212
  • [26] A Novel, Three-Stage Intelligent Fuzzy Traffic Signal Control System
    Chala, Tamrat D.
    Koczy, Laszlo T.
    ACTA POLYTECHNICA HUNGARICA, 2024, 21 (08) : 189 - 209
  • [27] Development of an electrode intelligent design system based on adaptive fuzzy neural network and genetic algorithm
    Huang, J. (huangjun0061@126.com), 1600, (23):
  • [28] Intelligent Pet House Environment Control System Based on Decoupling Fuzzy Neural Network
    Song, Chun-feng
    Wang, Xin-xue
    ARTIFICIAL INTELLIGENCE AND ROBOTICS, ISAIR 2023, 2024, 1998 : 443 - 453
  • [29] AN INTELLIGENT CONTROL SYSTEM BASED ON RECURRENT NEURAL FUZZY NETWORK AND ITS APPLICATION TO CSTR
    JIA Li YU Jinshou (Research Institute of Automation
    East China University of Science and Technology
    Shanghai
    Journal of Systems Science and Complexity, 2005, (01) : 43 - 54
  • [30] AN INTELLIGENT CONTROL SYSTEM BASED ON RECURRENT NEURAL FUZZY NETWORK AND ITS APPLICATION TO CSTR
    JIA Li YU Jinshou (Research Institute of Automation
    Journal of Systems Science & Complexity, 2005, (01) : 43 - 54
12345