… solutions, existing approaches on urban intersections heavily rely on domain knowledge …
decentralized bi-directional hierarchical reinforcement learning framework by regarding TLs …

… Schneider, and JM Dolan, “Hierarchical reinforcement learning method for autonomous
vehicle behavior planning,” in 2020 IEEE/RSJ International Conference on Intelligent Robots …

… In this work we developed a solution to car’s movement on road intersection. For that we
made a new environment to simulate a process and applied a hierarchical reinforcement …

… hierarchical reinforcement learning-based decision-making architecture for learning left-turn
policies at unsignalized intersections … avoidance with the intersection vehicles, whereas the …

… intelligent vehicles in complex urban environments. Based on the performed literature survey,
it is intended to use hierarchical reinforcement … at urban unsignalized intersections. There …

… Hierarchical Reinforcement Learning (HRL) and Options Framework to control a signalized
vehicular intersection … The proposed model uses intelligent agents that acquire knowledge …

… Given that the wide-area situational awareness is enabled by advanced information and
communication technologies, this paper develops a hierarchical operation framework for …

… intersection of the city of Ottawa to build our simulations and show that, clustering the network
using hierarchal … with implementing intelligent controllers using reinforcement learning is …

Multi-agent reinforcement learning (MARL) is a promising algorithm for traffic signal control (TSC),
and graph neural networks make a further improvement on its learning capacity. …

… a four-approach intersection (phase setting of different kinds of intersections may be different)…
of an intersection is average time vehicles spent on the local area of the intersection, while …