Model predictive control-based lane change control system for an autonomous vehicle

Chao Huang, Fazel Naghdy, Haiping Du

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

15 Citations (Scopus)


Autonomous vehicle have attracted more attention in recent years as vehicle applications are evolving to a more intelligent and autonomous stage. Lane-change maneuverer is one of the most thoroughly investigated automatic driving operations for autonomous vehicle. This paper presents a lane change control system for an autonomous vehicle which consists of a path generator and model-predictive-control-based vehicle steering and wheel torque control. The path generator, based on convex optimization, generates a collision-free trajectory when a vehicle collision with vehicles in a two-way path is likely. The lane change manoeuver for collision avoidance is performed using the MPC-based control system to control the front wheel angle, rear wheel angles and individual wheel torques to track the desired path. The proposed system is evaluated through simulation by using an eight-degrees-of-freedom vehicle model and Dugoff tire model.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509025961
Publication statusPublished - 22 Nov 2016
Externally publishedYes
Event2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore
Duration: 22 Nov 201625 Nov 2016

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450


Conference2016 IEEE Region 10 Conference, TENCON 2016


  • autonomous vehicle
  • Lane change control
  • model predictive control
  • vehicle safety

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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