Műegyetemi Digitális Archívum
 

Double Lane Change Path Planning Using Reinforcement Learning with Field Tests

Date

Language

en

Reading access rights:

Open access

Rights Holder

Budapest University of Technology and Economics

Conference Date

2022.03.31

Conference Place

Budapest University of Technology and Economics

Conference Title

The First Conference on ZalaZONE Related R&I Activities of Budapest University of Technology and Economics 2022

ISBN, e-ISBN

ISBN 978-963-421-873-9

Container Title

Proceedings of The First Conference on ZalaZONE Related R&I Activities of Budapest University of Technology and Economics 2022

Department

Department of Automotive Technologies

Version

Kiadói változat

Faculty

Faculty of Transportation Engineering and Vehicle Engineering

First Page

67

Subject (OSZKAR)

Local path planning
Model predictive control
Reinforcement learning
Vehicle dynamics

University

Budapest University of Technology and Economics

OOC works

Abstract

Performing dynamic double lane-change maneuvers can be a challenge for highly automated vehicles. The algorithm must meet safety requirements while keeping the vehicle stable and controllable. The problem of path planning is numerically complex and must be run at a high refresh rate. The article presents a new approach to avoiding obstacles for autonomous vehicles. To solve this problem

Description

Keywords