Reinforcement learning (RL) is a method which provides true learning capabilities regarding situation-based actions. RL-systems explore and self-optimise actions for situations in a defined environment. This paper describes the research of a driver (assistance) system based on pure reinforcement learning in the framework of an autonomous vehicle. The target of this research is to determine to what extent RL-based systems serve as an enhancement or even an alternative to classical concepts of autonomous intelligent vehicles such as modelling or neural nets.
Optimising situation-based behaviour of autonomous vehicles
01.01.2004
809984 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
MPP1.19 Optimising Situation-Based Behaviour of Autonomous Vehicles
British Library Conference Proceedings | 2004
|Situation awareness for autonomous vehicles using blockchain-based service cooperation
BASE | 2022
|Optimising Hybrid-Electric Vehicles for Europe
British Library Conference Proceedings | 1998
|Optimising hybrid-electric vehicles for Europe
Tema Archiv | 1998
|