Dynamic network congestion pricing based on deep reinforcement learning. (arXiv:2206.12188v1 [eess.SY])

Traffic congestion is a serious problem in urban areas. Dynamic congestion
pricing is one of the useful schemes to eliminate traffic congestion in
strategic scale. However, in the reality, an optimal dynamic congestion pricing
is very difficult or impossible to determine theoretically, because road
networks are usually large and complicated, and behavior of road users is
uncertain. To account for this challenge, this work proposes a dynamic
congestion pricing method using deep reinforcement learning (DRL). It is
designed to eliminate …

arxiv congestion learning network pricing reinforcement reinforcement learning