Real-Time Traffic Signal Control for Roundabouts by Using a PSO-Based Fuzzy Controller

被引:0
|
作者
Gong, Yue-jiao [1 ]
Zhang, Jun [1 ]
机构
[1] Sun Yat Sen Univ, Key Lab Software Technol, Key Lab Digital Life, Dept CS,Minist Educ,Educ Dept Guangdong Prov, Guangzhou, Guangdong, Peoples R China
关键词
fuzzy logic; membership function; particle swarm optimization (PSO); roundabout; traffic control;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Developing traffic signal control methods is considered as the most important way to improve the traffic efficiency of modern roundabouts. This paper applies a traffic signal controller with two fuzzy layers for signalizing roundabouts. The outer layer of the controller computes urgency degrees of all the phase subsets and then activates the most urgent subset. This mechanism helps to instantly respond to the current traffic condition of the roundabout so as to improve real-timeness. The inner layer computes extension time of the current phase and decides whether to turn to the next phase in the running phase subset. As the phase sequences are well-designed, the inner layer smoothes the traffic flows which helps to avoid traffic jam. An offline particle swarm optimization (PSO) algorithm is developed to optimize the membership functions adopted in the proposed controller. In this way, the membership functions in the controller are no longer given by human experience, but provided by the intelligent algorithm. Simulation results demonstrate that the proposed controller outperforms previous traffic signal controllers in terms of improving traffic efficiency of modern roundabouts.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Optimized Timing Parameters for Real-Time Adaptive Traffic Signal Controller
    Aljaafreh, Ahmad
    Al-Oudat, Naeem
    [J]. 2014 UKSIM-AMSS 16TH INTERNATIONAL CONFERENCE ON COMPUTER MODELLING AND SIMULATION (UKSIM), 2014, : 244 - 247
  • [22] Real-time control of ball balancer using neural integrated fuzzy controller
    Rupam Singh
    Bharat Bhushan
    [J]. Artificial Intelligence Review, 2020, 53 : 351 - 368
  • [23] Real-time control of ball balancer using neural integrated fuzzy controller
    Singh, Rupam
    Bhushan, Bharat
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2020, 53 (01) : 351 - 368
  • [24] PSO-Based PI Controller for Speed Sensorless Control of PMSM
    Nazelan, A. M.
    Osman, M. K.
    Samat, A. A. A.
    Salim, N. A.
    [J]. 1ST INTERNATIONAL CONFERENCE ON GREEN AND SUSTAINABLE COMPUTING (ICOGES) 2017, 2018, 1019
  • [25] Real-time traffic signal control for optimization of traffic jam probability
    Cui, Cheng-You
    Shin, Ji-Sun
    Miyazaki, Michio
    Lee, Hee-Hyol
    [J]. ELECTRONICS AND COMMUNICATIONS IN JAPAN, 2013, 96 (01) : 1 - 13
  • [26] Real-time traffic signal settings at an isolated signal control intersection
    Vilarinho, Cristina
    Tavares, Jose Pedro
    [J]. 17TH MEETING OF THE EURO WORKING GROUP ON TRANSPORTATION, EWGT2014, 2014, 3 : 1021 - 1030
  • [27] Cost Effective Real-Time Traffic Signal Control Using the TUC Strategy
    Kraus, Werner, Jr.
    de Souza, Felipe Augusto
    Kosmatopoulos, Elias B.
    Carlson, Rodrigo Castelan
    Papageorgiou, Markos
    Camponogara, Eduardo
    Dantas, Luciano Dionisio
    Aboudolas, Konstantinos
    [J]. IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2010, 2 (04) : 6 - 17
  • [28] Real-time control via an adaptive hierarchical fuzzy controller
    Tsang, MW
    Rad, AB
    [J]. PROCEEDINGS OF THE SIXTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS I - III, 1997, : 981 - 986
  • [29] Multi-agent fuzzy signal control based on real-time simulation
    Kosonen, I
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2003, 11 (05) : 389 - 403
  • [30] Fuzzy Bionic Hand Control in Real-Time Based on Electromyography Signal Analysis
    Tabakov, Martin
    Fonal, Krzysztof
    Abd-Alhameed, Raed A.
    Qahwaji, Rami
    [J]. COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2016, PT I, 2016, 9875 : 292 - 302