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Artificial Intelligence in Traffic Management - Selected Examples
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AI
DOI：10.3233/ATDE251541.png)
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Abstract
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The application of artificial intelligence (AI) in traffic management is expanding rapidly, offering innovative ways to optimize urban transportation systems. This paper provides a concise overview of key AI-driven traffic control strategies - including congestion forecasting, dynamic rerouting, and adaptive traffic signal control - that aim to reduce congestion and improve road safety. We combine insights from global research with case studies from Polish cities to highlight the practical benefits and challenges of implementing these AI solutions in real traffic systems. Our analysis confirms that early AI deployments are already yielding measurable improvements in traffic flow efficiency and safety. Looking ahead, integrating AI with connected and autonomous vehicles and with multimodal transport networks promises to further enhance the efficiency, safety, and sustainability of urban mobility.
Keywords:
AI
traffic
traffic management
Machine Learning
traffic jam
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