Derin Pekiştirmeli Öǧrenme Kullanan Belirsizlik Altinda Karar Verme Odakli Otonom Sürüş Sistemleri

Translated title of the contribution: Autonomous Driving Systems for Decision-Making Under Uncertainty Using Deep Reinforcement Learning

Mehmet Haklidir, Hakan Temeltas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Deep reinforcement learning has achieved human-level and even beyond performance on complex tasks like Atari games and Go. However, this performance is not easy to adapt to autonomous driving since real world state spaces are extremely complex and have continuous action spaces. Besides, autonomous driving tasks often require decision making under uncertainty. Hence, the autonomous driving problem can be formulated as a partially observable Markov decision process (POMDP).In this paper, we propose a new approach to solve the autonomous driving problem based on decision making under uncertainty as a partially observable Markov decision process, using Guided Soft Actor-Critic (Guided SAC). Self driving car has been trained for the scenario where it encountered with a pedestrian crossing the road. Experiments show that the control agent exhibits desirable control behavior and performed close to the fully observable state under various uncertainty situations.

Translated title of the contributionAutonomous Driving Systems for Decision-Making Under Uncertainty Using Deep Reinforcement Learning
Original languageTurkish
Title of host publication2022 30th Signal Processing and Communications Applications Conference, SIU 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665450928
DOIs
Publication statusPublished - 2022
Event30th Signal Processing and Communications Applications Conference, SIU 2022 - Safranbolu, Turkey
Duration: 15 May 202218 May 2022

Publication series

Name2022 30th Signal Processing and Communications Applications Conference, SIU 2022

Conference

Conference30th Signal Processing and Communications Applications Conference, SIU 2022
Country/TerritoryTurkey
CitySafranbolu
Period15/05/2218/05/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

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