Optimal longitudinal control planning with moving obstacles

Jeff Johnson, Kris Hauser

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


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
Number of pages7
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


Conference2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
CityGold Coast, QLD

ASJC Scopus subject areas

  • Modeling and Simulation
  • Automotive Engineering
  • Computer Science Applications


Dive into the research topics of 'Optimal longitudinal control planning with moving obstacles'. Together they form a unique fingerprint.

Cite this