Traffic signal control is a crucial element of urban mobility that profoundly influences transportation network efficiency and safety. Traditional traffic signal control systems rely on fixed-time or actuated signal timings, often failing to adapt to dynamic traffic demands and congestion patterns. This technical report explores the application of Reinforcement Learning (RL) algorithms to traffic signal control, aiming to enhance traffic flow efficiency and alleviate congestion.
This report provides a guideline to estimate the staffing and resource needs required to effectivelyoperate and maintain traffic signal systems. The r...
This report provides a roadmap to details contained in six TOSCo Phase 1 detailed reports that focus on specific aspects of the four key technical obj...
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United States Department of Transportation
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