Search-Based Motion Planning for Performance Autonomous Driving

Zlatan Ajanovic*, Enrico Regolin, Georg Stettinger, Martin Horn, Antonella Ferrara

*Corresponding author for this work

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

Abstract

Driving on the limits of vehicle dynamics requires predictive planning of future vehicle states. In this work, a search-based motion planning is used to generate suitable reference trajectories of dynamic vehicle states with the goal to achieve the minimum lap time on slippery roads. The search-based approach enables to explicitly consider a nonlinear vehicle dynamics model as well as constraints on states and inputs so that even challenging scenarios can be achieved in a safe and optimal way. The algorithm performance is evaluated in simulated driving on a track with segments of different curvatures. Our code is available at https://git.io/JenvB.

Original languageEnglish
Title of host publicationAdvances in Dynamics of Vehicles on Roads and Tracks - Proceedings of the 26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019
EditorsMatthijs Klomp, Fredrik Bruzelius, Jens Nielsen, Angela Hillemyr
PublisherSpringer
Pages1144-1154
Number of pages11
ISBN (Print)9783030380762
DOIs
Publication statusPublished - 1 Jan 2020
Event26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019 - Gothenburg, Sweden
Duration: 12 Aug 201916 Aug 2019

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

Conference26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019
CountrySweden
CityGothenburg
Period12/08/1916/08/19

Keywords

  • Autonomous vehicles
  • Drifting
  • Motion planning
  • Trail-braking

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

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