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Real‐time traffic signal control for optimization of traffic jam probability
Author(s) -
Cui ChengYou,
Shin JiSun,
Miyazaki Michio,
Lee HeeHyol
Publication year - 2013
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.11436
Subject(s) - traffic generation model , floating car data , traffic flow (computer networking) , computer science , real time computing , signal (programming language) , traffic congestion reconstruction with kerner's three phase theory , cellular automaton , particle swarm optimization , real time control system , network traffic control , probabilistic logic , simulation , control (management) , engineering , algorithm , traffic congestion , artificial intelligence , computer network , transport engineering , network packet , programming language
Real‐time traffic signal control is an integral part of an urban traffic control system. It can control traffic signals online according to variations of traffic flow. In this paper we propose a new method for a real‐time traffic signal control system. The system uses a cellular automaton model and a Bayesian network model to predict probabilistic distributions of standing vehicles, and uses particle swarm optimization to calculate the optimal traffic signals. A simulation based on real traffic data was carried out to show the effectiveness of the proposed CAPSOBN real‐time traffic signal control system using a micro traffic simulator. © 2012 Wiley Periodicals, Inc. Electron Comm Jpn, 96(1): 1–13, 2013; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ecj.11436