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Showing 1 to 2 of 2 for “"Traffic signs and signals--Control systems--Automation"”.
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Decentralized graph-based multi-agent reinforcement learning for traffic signal optimization
… 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 heterogeneous traffic conditions. This dissertation develops a decentralized …
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A mixed-integer linear programming (MILP) model for dynamic coordinated signal optimization along a traffic corridor
In this thesis, we address urban traffic congestion, which imposes substantial economic and environmental costs while traditional infrastructure solutions remain increasingly infeasible due to financial constraints and induced demand. We develop a dynamic Mixed-Integer Linear Programming (MILP) …