DocumentCode :
2023391
Title :
An apporach for analyzing queuing systems using Markov Chain Monte Carlo methods : A traffic flow case study
Author :
Xin Ci Wong ; Ahmed, Syed Khaleel ; Zulkift, Fadhilali ; Ramasamy, Agileswari K.
Author_Institution :
Dept. of Electron. & Commun. Eng., Univ. Tenaga Nasional, Kajang, Malaysia
fYear :
2009
fDate :
16-18 Nov. 2009
Firstpage :
41
Lastpage :
44
Abstract :
In our urban community, having to wait in line is a daily nuisance as precious time is wasted. One simple example is traffic congestion on roads. Reduction of these congestions will not only minimize time wastage but also lead to a healthier life. For this reason, various approaches have been taken to mitigate this problem. In this paper, a simulation approach is proposed to model and investigate the behavior of traffic flow on roads. This is due to the difficulty in obtaining exact solutions based on probability theory and queuing systems even for moderately complex systems. In this paper, the simulation technique used is based on the Markov Chain Monte Carlo technique. It is noticed that the result obtained shows that traffic behavior can be modeled accurately. Thus, this simple approach can be extended to other similar systems such as computer networks, communication systems, etc.
Keywords :
Markov processes; Monte Carlo methods; probability; queueing theory; road traffic; Markov chain Monte Carlo methods; communication systems; computer networks; probability theory; queuing systems; roads traffic congestion; traffic flow case study; Decision support systems; Queueing analysis; Traffic control; Virtual reality; Markov Chain; Monte Carlo; Queuing Systems; Simulation; Traffic Flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Research and Development (SCOReD), 2009 IEEE Student Conference on
Conference_Location :
UPM Serdang
Print_ISBN :
978-1-4244-5186-9
Electronic_ISBN :
978-1-4244-5187-6
Type :
conf
DOI :
10.1109/SCORED.2009.5443360
Filename :
5443360
Link To Document :
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