Knowledge intensive state design for traffic signal control. (arXiv:2201.00006v1 [cs.LG])

There is a general trend of applying reinforcement learning (RL) techniques
for traffic signal control (TSC). Recently, most studies pay attention to the
neural network design and rarely concentrate on the state representation. Does
the design of state representation has a good impact on TSC? In this paper, we
(1) propose an effective state representation as queue length of vehicles with
intensive knowledge; (2) present a TSC method called MaxQueue based on our
state representation approach; (3) develop a general …

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