Real-Time near-optimal path and maneuver planning in automatic parking using a simultaneous dynamic optimization approach

Jaeyoung Moon, Il Bae, Shiho Kim

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

8 Citations (Scopus)

Abstract

We propose a real-Time near-optimal motion and trajectory planner using an interior-point method (IPM) based simultaneous dynamic optimization approach applicable to automatic parallel parking. Partitioning an automatic parking zone into two areas with and without inequality constraints drastically improves the convergence efficiency of the IPM-based simultaneous dynamic optimization of nonlinear programs while retaining the accuracy and stability of simulation for optimization. An optimal ready-To-reverse point (RRP), from where backward moving parking maneuver starts, is provided based on the cost function of the tracking time and additional delayed time of gear shifts caused by multiple maneuvers. The stability and accuracy of the proposed method was verified through simulation using AMPL with an IPOPT solver.

Original languageEnglish
Title of host publicationIV 2017 - 28th IEEE Intelligent Vehicles Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages193-196
Number of pages4
ISBN (Electronic)9781509048045
DOIs
Publication statusPublished - 2017 Jul 28
Event28th IEEE Intelligent Vehicles Symposium, IV 2017 - Redondo Beach, United States
Duration: 2017 Jun 112017 Jun 14

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings

Other

Other28th IEEE Intelligent Vehicles Symposium, IV 2017
CountryUnited States
CityRedondo Beach
Period17/6/1117/6/14

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Automotive Engineering
  • Modelling and Simulation

Cite this

Moon, J., Bae, I., & Kim, S. (2017). Real-Time near-optimal path and maneuver planning in automatic parking using a simultaneous dynamic optimization approach. In IV 2017 - 28th IEEE Intelligent Vehicles Symposium (pp. 193-196). [7995719] (IEEE Intelligent Vehicles Symposium, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IVS.2017.7995719