Merging control for automated vehicles using decentralized model predictive control

Yasuhiro Hayashi, Toru Namerikawa

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

2 Citations (Scopus)

Abstract

Ahstract-This paper deals with merging control of automated vehicles using distributed model predictive control. We consider a road model which has two main lanes. In the distributed control algorithm, vehicles repeat sharing the planned future trajectory with other vehicles traveling in the vicinity of each vehicle by using communication and replanning its own trajectory considering the future trajectory of other vehicles. Moreover, in order to further improve the stability of model predictive control, terminal constraints are set and feasible conditions for optimization problems under the terminal conditions are derived. At the last part of this paper, we confirm the effectiveness of proposed methods through simulations.

Original languageEnglish
Title of host publicationAIM 2018 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages268-273
Number of pages6
Volume2018-July
ISBN (Print)9781538618547
DOIs
Publication statusPublished - 2018 Aug 30
Event2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2018 - Auckland, New Zealand
Duration: 2018 Jul 92018 Jul 12

Other

Other2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2018
CountryNew Zealand
CityAuckland
Period18/7/918/7/12

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications
  • Software

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  • Cite this

    Hayashi, Y., & Namerikawa, T. (2018). Merging control for automated vehicles using decentralized model predictive control. In AIM 2018 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics (Vol. 2018-July, pp. 268-273). [8452265] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AIM.2018.8452265