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Reseach Article

Speed Range Prediction for Traffic Light Control System

by Prashant Borkar, Sanjeevani Jenekar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 3
Year of Publication: 2012
Authors: Prashant Borkar, Sanjeevani Jenekar
10.5120/8550-2110

Prashant Borkar, Sanjeevani Jenekar . Speed Range Prediction for Traffic Light Control System. International Journal of Computer Applications. 54, 3 ( September 2012), 61-65. DOI=10.5120/8550-2110

@article{ 10.5120/8550-2110,
author = { Prashant Borkar, Sanjeevani Jenekar },
title = { Speed Range Prediction for Traffic Light Control System },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 3 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 61-65 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number3/8550-2110/ },
doi = { 10.5120/8550-2110 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:47.632005+05:30
%A Prashant Borkar
%A Sanjeevani Jenekar
%T Speed Range Prediction for Traffic Light Control System
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 3
%P 61-65
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper discuses a proposed systems for acquiring the next intersection timing and generating the required speed at current intersection to cross next intersection without stopping at it. The system is speed module for next intersection prediction embedded in intelligent traffic light control system at intersection. It can also be designed for GPS based navigation system. For efficiently predicting the time and speed required for crossing next intersection without stopping at it centralized approach is taken into account, the distance between current intersection and next intersection and traffic signal timings of next intersection are considered as input to the system. The traffic signal timings are more on highway than on city road. System then generates the required speed in range to cross next intersection without stopping at it. Speed generated by the system is in specified range like 32Km/Hr to 40 Km/Hr. Also it can't exceed the speed limit of road.

References
  1. Holger Prothmann, Jürgen Branke and Hartmut Schmeck "Organic traffic light control for urban road networks " Int. J. Autonomous and Adaptive Communications Systems, Vol. 2, No. 3, 2009.
  2. Pitu Mirchandani, Fei-Yue Wang "RHODES to Intelligent Transportation Systems" 1541-1672/05/ © 2005 IEEE. IEEE INTELLIGENT SYSTEMS
  3. Xiangjie Kong, Guojiang Shen, Feng Xia, and Chuang LinUrban. "Arterial Traffic Two-direction Green Wave Intelligent Coordination Control Technique and Its Application" International Journal of Control, Automation, and Systems (2011) 9(1):60-68
  4. W. Wen. "A dynamic and automatic traffic light control expert system for solving the road congestion problem" 2007 Elsevier Ltd. All rights reserved. doi:10. 1016/j. eswa. 2007. 03. 007. science direct a Expert Systems with Applications 34 (2008) 2370–2381
  5. Chunxiao LI, Shigeru SHIMAMOTO. "A Real Time Traffic Light Control Scheme for Reducing Vehicles CO2 Emissions" The 8th Annual IEEE Consumer Communications and Networking Conference - Emerging and Innovative Consumer Technologies and Applications.
  6. Chen Xiao-feng, Shi Zhong-ke, Zhao Kai "Research on an Intelligent Traffic Signal Controller" 0-7803-8125-4/03 © 2003 IEEE
  7. Liu Zhiyong, et al. A Multi-phase Fuzzy Control Method Used for Single Intersection. Information and Control, 1999, 28(6): pp. 453-458
  8. Liu Zhiyong et al. "Hierarchical Fuzzy Control for Urban Traffic Trunk Roads. " Journal of Highway and Transportation Research and Development, 1997, 14(3): pp. 17-23.
  9. Dong Chaojun, Liu Zhiyong, et al. "Urban Traffic Signal Timing Optimization Based on Multi-layer Chaos Neural Networks Involving Feedback," Proc. Of First International Conference on Natural Computation, ICNC 2005, pp. 340-344
  10. M. Wiering. "Multi-Agent Reinforcement Learning for Traffic Light Control. Machine Learning," Proc. of the Seventeenth International Conference (ICML'2000), pp. 1151-1158
  11. M. Wiering, et al. "Intelligent Traffic Light Control," Technical Report UU-CS-2004-029, University Utrecht, 2004.
  12. N. MASLEKAR et al. "VANET based Adaptive Traffic Signal Control," IEEE 2011.
  13. Fuqiang Zou et al, "Traffic Light Control for a single intersection based on Wireless Sensor Network," The Ninth International Conference on Electronic Measurement & Instruments, IEEE 2009
Index Terms

Computer Science
Information Sciences

Keywords

Traffic congestion Intersection Traffic signal required speed