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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Veröffentlicht in:	IEEE access 2022, Vol.10, p.53601-53613
Hauptverfasser:	Guillen-Perez, Antonio, Cano, Maria-Dolores
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximation algorithms Autonomous intersection management Autonomous vehicles Behavioral sciences Control algorithms Corporate learning Deep learning Electricity consumption intelligent transport systems intersection traffic management learning from demonstrations Machine learning multi-agent deep reinforcement learning Multiagent systems Performance measurement Policies Proposals Reinforcement learning Task analysis Traffic intersections Traffic management Training
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