Reinforcement Learning For Adaptive Traffic Signal Control
نویسنده
چکیده
By 2050, two-thirds of the world’s 9.6 billion people will live in urban areas [2]. In many cities, opportunities to expand urban road networks are limited, so existing roads will need to more efficiently accommodate higher volumes of traffic. Consequently, there is a pressing need for technologically viable, low-cost solutions that can work with existing infrastructure to help alleviate increasing traffic congestion.
منابع مشابه
Adaptive Traffic Signal Control: Deep Reinforcement Learning Algorithm with Experience Replay and Target Network
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