Trajectory optimization for autonomous overtaking with visibility maximization

Hans Andersen, Wilko Schwarting, Felix Naser, You Hong Eng, Marcelo H. Ang, Daniela Rus, Javier Alonso-Mora

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

14 Citations (Scopus)


In this paper we present a trajectory generation method for autonomous overtaking of static obstacles in a dynamic urban environment. In these settings, blind spots can arise from perception limitations. For example, the autonomous car may have to move slightly into the opposite lane in order to cleanly see in front of a car ahead. Once it has gathered enough information about the road ahead, then the autonomous car can safely overtake. We generate safe trajectories by solving, in real-time, a non-linear constrained optimization, formulated as a Receding Horizon planner. The planner is guided by a high-level state machine, which determines when the overtake maneuver should begin. Our main contribution is a method that can maximize visibility, prioritizes safety and respects the boundaries of the road while executing the maneuver. We present experimental results in simulation with data collected during real driving.

Original languageEnglish
Title of host publicationProceedings 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC 2017)
Place of PublicationPiscataway, NJ, USA
Number of pages8
ISBN (Electronic)978-1-5386-1525-6
Publication statusPublished - 2017
Event20th IEEE International Conference on Intelligent Transport Systems, ITSC 2017 - Mielparque Yokohama, Yokohama, Japan
Duration: 16 Oct 201719 Oct 2017
Conference number: 20


Conference20th IEEE International Conference on Intelligent Transport Systems, ITSC 2017
Abbreviated titleITSC 2017
Internet address


  • Trajectory
  • Autonomous vehicles
  • Roads
  • Urban areas
  • Vehicle dynamics
  • Planning
  • Optimization

Fingerprint Dive into the research topics of 'Trajectory optimization for autonomous overtaking with visibility maximization'. Together they form a unique fingerprint.

Cite this