An apporach for analyzing queuing systems using Markov chain Monte Carlo methods: A traffic flow case study

• Main Authors: Wong X.C., Ahmed S.K., Zulkifli F., Ramasamy A.K.
• Other Authors: 36070257800
• Format: Conference Paper
• Published: 2023
• Subjects: Markov chain; Monte Carlo; Queuing systems; Simulation; Traffic flow; Communication systems; Flow simulation; Markov processes; Queueing networks; Queueing theory; Research; Roads and streets; Complex systems; Exact solution; In-line; Markov chain Monte Carlo; Markov chain Monte Carlo method; Markov chain Monte Carlo techniques; Probability theory; Simple approach; Simulation approach; Simulation technique; Traffic behavior; Urban community; Monte Carlo methods

In our urban community, having to wait In line Is a dally 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. �2009 IEEE.