Policy Gradient Based Reinforcement Learning Approach for Autonomous Highway Driving

Szilard Aradi, Tamas Becsi, P. Gáspár

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

5 Citations (Scopus)

Abstract

The paper presents the application of the Policy Gradient reinforcement learning method in the area of vehicle control. The purpose of the research presented is to design an end-to-end behavior control of a kinematic vehicle model placed in a simulated highway environment, by using reinforcement learning approach. The environment model for the surrounding traffic uses microscopic simulation to provide different situations for the agent. The environment sensing model is based on high-level sensor information, e.g. the odometry, lane position and surrounding vehicle states that can be reached from the current automotive sensors, such as camera and radar based systems. The objectives were reached through the definition of a rewarding system, with subrewards and penalties enforcing desired speed, lane keeping, keeping right and avoiding collision. After the description of the theoretical basis the environment model with the reward function is detailed. Finally the experiments with the learning process are presented and the results of the evaluation are given from some aspects of control quality and safety.

Original languageEnglish
Title of host publication2018 IEEE Conference on Control Technology and Applications, CCTA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages670-675
Number of pages6
ISBN (Electronic)9781538676981
DOIs
Publication statusPublished - Oct 26 2018
Event2nd IEEE Conference on Control Technology and Applications, CCTA 2018 - Copenhagen, Denmark
Duration: Aug 21 2018Aug 24 2018

Other

Other2nd IEEE Conference on Control Technology and Applications, CCTA 2018
CountryDenmark
CityCopenhagen
Period8/21/188/24/18

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ASJC Scopus subject areas

  • Aerospace Engineering
  • Control and Optimization
  • Automotive Engineering
  • Safety, Risk, Reliability and Quality

Cite this

Aradi, S., Becsi, T., & Gáspár, P. (2018). Policy Gradient Based Reinforcement Learning Approach for Autonomous Highway Driving. In 2018 IEEE Conference on Control Technology and Applications, CCTA 2018 (pp. 670-675). [8511514] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCTA.2018.8511514