Traffic Management of Autonomous Vehicles using Policy Based Deep Reinforcement Learning and Intelligent Routing. (arXiv:2206.14608v1 [cs.LG])

Deep Reinforcement Learning (DRL) uses diverse, unstructured data and makes
RL capable of learning complex policies in high dimensional environments.
Intelligent Transportation System (ITS) based on Autonomous Vehicles (AVs)
offers an excellent playground for policy-based DRL. Deep learning
architectures solve computational challenges of traditional algorithms while
helping in real-world adoption and deployment of AVs. One of the main
challenges in AVs implementation is that it can worsen traffic congestion on
roads if not reliably and efficiently managed. Considering each vehicle's …

arxiv autonomous autonomous vehicles intelligent learning lg management policy reinforcement reinforcement learning routing traffic traffic management