Abstract

Lane keeping controller drives vehicle's steering to keep the vehicle driving on the track. This paper discusses lane control on a prototype autonomous car that moves at constant speed, using a nonlinear predictive control (MPC) model which is used to calculate the optimal steering angle based on lateral deviation information. The predictive lateral deviations are obtained from the linear parameter varying (LPV) model while the current lateral deviation value is obtained from the lane detection algorithm which produces a reference trajectory for the car. The lane detection uses image processing towards images captured by the camera. The real time experiment result shows that the proposed controller could keep the prototype to stay on track until the curvature of 0.27 m-1 with the maximum lateral deviation of 8.86 cm.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages12-16
Number of pages5
ISBN (Electronic)9781665497428
DOIs
Publication statusPublished - 2022
Event6th IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022 - Virtual, Malang, Indonesia
Duration: 16 Jun 202218 Jun 2022

Publication series

NameProceedings - 2022 IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022

Conference

Conference6th IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCom 2022
Country/TerritoryIndonesia
CityVirtual, Malang
Period16/06/2218/06/22

Keywords

  • Autonomous Car
  • Image Processing
  • Lane Keeping Controller
  • Model Predictive Control

Fingerprint

Dive into the research topics of 'Lane Keeping Control Using Nonlinear Model Predictive Control on Constant Speed Autonomous Car'. Together they form a unique fingerprint.

Cite this