AI-Driven Traffic Control Systems For Smart Cities In Civil Engineering

Fast city growth and the huge rise in vehicle numbers are putting a lot of pressure on current road networks. This leads to regular traffic jams, more accidents, and higher pollution. To tackle these problems, civil engineers are adding Intelligent Traffic Management Systems (ITMS) to smart‑city plans. The research looks at using Artificial Intelligence (AI) and the Internet of Things (IoT) to create traffic‑control systems that react to data in real time. By gathering live data from sensor networks spread across the city and from automated vehicles, the systems can see what’s happening on the road and adjust traffic‑light timings for smoother flow. The project gives step‑by‑step guidance for: –

modeling adaptive traffic‑control algorithms, – simulating coordination across multiple intersections, and – measuring how AI‑driven actions affect queue lengths, travel delays, and vehicle emissions. Detailed simulations and performance checks help build traffic networks that can expand, stay reliable, reduce congestion, and later support autonomous vehicles. Graduate students can use this framework to set up simulation models that test AI traffic‑control strategies under different demand scenarios.

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