MATLAB SimEvent for Traffic Queue Model
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Distributive Statistics

How to Cite

Anyin, P. B., Anyin, P. B., & Murana, A. A. (2024). MATLAB SimEvent for Traffic Queue Model. ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY AND ENVIRONMENT, 20(1), 161-172. Retrieved from


The use of MATLAB (SimEvent) for network performance measure determination is encouraged by the novel precision that comes with artificial intelligence techniques. However, most efforts in this direction have been undervalued due to distribution assumptions. Therefore, a comparative analysis with an analytical method is studied in this work, with service rate distribution determined, using a distributive StatAssist tool. Kendall’s model adopted was M/M/1 for a single server queueing system and was confirmed by the service rate distributive pattern as 1.0 second per customer. Estimating the network measures showed analytical and simulation models hourly average queue length of 3,751 vehicles, with 1hr and 11minutes waiting time. The total daily queueing length is 8419vehicles, with 8819secs total waiting time. The utilization factor of 0.984 and the model is found to be 0.9825/1.025/1. From the optimum determination of the analytical model (AM) and simulation model (SM) weekly performance measures carried out, the AM produced the following average waiting time 3751, 125, 56, 35, 110, 19, and 17, from Monday through Sunday. In contrast, the SM produced an average waiting time of 3681, 3007, 2789, 2567, 2854, 2467, and 1976 respectively. Due to the continuous waiting line output, the SM has proven realistic. Therefore, the Simulation model coupled with distributive StatAssist tool is recommended for queueing studies. A comparative study of simulators is recommended for further studies.

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