Learning From Oracle Demonstrations—A New Approach to Develop Autonomous Intersection Management Control Algorithms Based on Multiagent Deep Reinforcement Learning

Learning From Oracle Demonstrations—A New Approach to Develop Autonomous Intersection Management Control Algorithms Based on Multiagent Deep Reinforcement Learning

Worldwide, many companies are working towards safe and innovative control systems for Autonomous Vehicles (AVs). A key component is Autonomous Intersection Management (AIM) systems, which operate at the level of traffic intersections and manage the right-of-way for AVs, thereby improving flow and sa...

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Bibliographic Details
Main Authors: Antonio Guillen-Perez, Maria-Dolores Cano
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Autonomous intersection management
intelligent transport systems
intersection traffic management
learning from demonstrations
multi-agent deep reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/9775674/

Internet

https://ieeexplore.ieee.org/document/9775674/

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