Optimal longitudinal control planning with moving obstacles

Jeff Johnson, Kris Hauser

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

Abstract

At intersections and in merging traffic, intelligent road vehicles must solve challenging optimal control problems in real-time to navigate reliably around moving obstacles. We present a complete planner that computes collision-free, optimal longitudinal control sequences (acceleration and braking) using a novel visibility graph approach that analytically computes the reachable subset of path-velocity-time space. We demonstrate that our method plans over an order of magnitude faster than previous approaches, making it scalable and fast enough (tenths of a second on a PC) to be called repeatedly on-line. We demonstrate applications to autonomous driving and vehicle collision warning systems with many moving obstacles.

Original languageEnglish (US)
Title of host publication2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
Pages605-611
Number of pages7
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013 - Gold Coast, QLD, Australia
Duration: Jun 23 2013Jun 26 2013

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings

Conference

Conference2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
Country/TerritoryAustralia
CityGold Coast, QLD
Period6/23/136/26/13

ASJC Scopus subject areas

  • Modeling and Simulation
  • Automotive Engineering
  • Computer Science Applications

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