Global ETD Search
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Showing 1 to 2 of 2 for “"Adaptive traffic signal control"”.
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Decentralized graph-based multi-agent reinforcement learning for traffic signal optimization
Signalized intersections are persistent bottlenecks where inefficient operations contribute to congestion, delays, safety risks, and environmental impacts. Conventional control strategies provide stability under predictable demand but lack the adaptability required to manage stochastic and …
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eMARLIN: Addressing Coordination and Partial Observability in Distributed Reinforcement Learning for Traffic Signal Control
Traffic congestion is a growing concern in urban areas, pertaining to its significant economic, environmental, and safety impacts. While traditional solutions like infrastructure expansion and public transit development are vital, they involve high budget and time costs. This thesis aims to address …