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Design and Evaluation of Optimization Algorithms for Adaptive Traffic Signal Control and Scalable Simulation of Large-Scale Traffic Networks

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Results show that optimization algorithms significantly reduce average delays compared to traditional methods.
Key performance metrics reveal consistent improvements in throughput and queue lengths during peak traffic scenarios.
Observational analysis across various traffic demand scenarios highlights the scalability and effectiveness of the framework.
Research indicates potential for future intelligent traffic management systems built on adaptive control strategies.

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Evaluation of optimization algorithms improves traffic throughput in urban networks, suggesting better real-time management.

Bosire et al. (2025) studied this question.

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