Modeling and Simulation of Urban Traffic Signals

Salimifard, Khodakaram; Ansari, Mehdi · 2013 · OpenAlex-citations

DOI: 10.7763/ijmo.2013.v3.261

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Summary

This paper addresses the challenge of modeling and simulating urban traffic signal systems using Arena, a discrete event simulation software not originally designed for traffic control. The authors aim to demonstrate that Arena can effectively model complex traffic intersections despite this limitation, providing a tool for analyzing traffic flow and evaluating control policies. The motivation stems from the critical role traffic signals play in managing congestion, reducing delays, and minimizing pollution, as well as the need for reliable models to support real-time control strategies. The study employs a case study of a major intersection in Bushehr, Iran, involving four streets: Emam, Bazargani, Bahonar, and Helali. The authors constructed a simulation model using Arena 10, utilizing 16 modules including Create, Process, Decide, and Dispose to represent vehicle arrivals, traffic light operations, branching probabilities, and departures. Data collection involved observing real operational policies to define arrival rates and branching percentages. The simulation covered a one-week period, tracking metrics such as average waiting times, queue lengths, and vehicle distribution. The authors also conducted scenario analysis by testing ten different timing policies for green light durations to evaluate their impact on system performance. The results indicate that the Arena model successfully captured the dynamics of the intersection. Average waiting times varied by street, with Helali Street vehicles waiting approximately 13.9 seconds and Emam Street vehicles waiting 26 seconds. Queue length analysis identified the path from Emam Street to Bazargani Street as the system bottleneck, with an average queue of 11.75 vehicles. Scenario analysis revealed that different timing policies significantly affected queue lengths across all streets. Specifically, Scenario 5 yielded the best overall performance, resulting in the lowest total queue length and representing an ideal condition for the system. In contrast, other scenarios, such as Scenario 9, produced higher queues on specific streets, highlighting the sensitivity of traffic flow to signal timing. The significance of this work lies in validating Arena as a viable tool for urban traffic simulation, expanding its application beyond traditional manufacturing and service systems. The findings provide a basis for optimizing traffic signal control policies to improve traffic fluidity and reduce congestion. By demonstrating that discrete event simulation can effectively model traffic intersections, the paper supports the use of simulation as a cost-effective method for evaluating control strategies and enhancing transportation system efficiency. This approach offers a practical framework for urban planners and traffic engineers to test and refine signal timing policies before implementation.

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• mental model of traffic