Reinforcement Learning for Autonomous Vehicle using MPC in Highway Situation

Yujin Kim, Dong Sung Pae, Sun Ho Jang, Seong Woo Kang, Myo Taeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Path planning for Autonomous Vehicle(AV) is a challenging problem, as the vehicle is required to obey the traffic rules while avoiding the collision with the other vehicles. Model Predictive Control(MPC) is one of the popular approach for proposing a feasible and stable path by reflecting vehicle dynamics in solving objective function and constraining the expected future control input. However, one of the drawbacks with this approach is that the demanded computational power increases proportionally to the number of considered future inputs. This paper presents a path planning algorithm using Reinforcement Learning(RL). RL is similar to MPC in finding the optimal solution that maximizes the reward function which can be seen as intrinsic objective function. In that respect, adequate employment of MPC path in training resulted in improved efficiency and performance. Through the simulations, proposed method showed 98% of similarity with path of MPC and reduced computation time by 91.13% on average, thus it is qualified for real-time path planning.

Original languageEnglish
Title of host publication2022 International Conference on Electronics, Information, and Communication, ICEIC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665409346
DOIs
Publication statusPublished - 2022
Event2022 International Conference on Electronics, Information, and Communication, ICEIC 2022 - Jeju, Korea, Republic of
Duration: 2022 Feb 62022 Feb 9

Publication series

Name2022 International Conference on Electronics, Information, and Communication, ICEIC 2022

Conference

Conference2022 International Conference on Electronics, Information, and Communication, ICEIC 2022
Country/TerritoryKorea, Republic of
CityJeju
Period22/2/622/2/9

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Autonomous vehicle
  • MPC
  • Path planning
  • Reinforcement learning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Reinforcement Learning for Autonomous Vehicle using MPC in Highway Situation'. Together they form a unique fingerprint.

Cite this