A Comparison Between Coupled and Decoupled Vehicle Motion Controllers Based on Prediction Models

Jose A. Matute, Ray Lattarulo, Asier Zubizarreta, Joshue Perez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)
31 Downloads (Pure)

Abstract

In this work, a comparative study is carried out with two different predictive controllers that consider the longitudinal jerk and steering rate change as additional parameters, as additional parameters, so that comfort constraints can be included. Furthermore, the approaches are designed so that the effect of longitudinal and lateral motion control coupling can be analyzed. This way, the first controller is a longitudinal and lateral coupled MPC approach based on a kinematic model of the vehicle, while the second is a decoupled strategy based on a triple integrator model based on MPC for the longitudinal control and a double proportional curvature control for the lateral motion control. The control architecture and motion planning are exhaustively explained. The comparative study is carried out using a test vehicle, whose dynamics and low-level controllers have been simulated using the realistic simulation environment Dynacar. The performed tests demonstrate the effectiveness of both approaches in speeds higher than 30 km/h, and demonstrate that the coupled strategy provides better performance than the decoupled one. The relevance of this work relies in the contribution of vehicle motion controllers considering the comfort and its advantage over decoupled alternatives for future implementation in real vehicles.
Original languageEnglish
Title of host publicationunknown
PublisherIEEE
Pages1843-1848
Number of pages6
ISBN (Electronic)978-1-7281-0560-4, 9781728105604
ISBN (Print)978-1-7281-0561-1
DOIs
Publication statusPublished - Jun 2019
Event30th IEEE Intelligent Vehicles Symposium, IV 2019 - Paris, France
Duration: 9 Jun 201912 Jun 2019

Publication series

Name2019-June

Conference

Conference30th IEEE Intelligent Vehicles Symposium, IV 2019
Country/TerritoryFrance
CityParis
Period9/06/1912/06/19

Keywords

  • Vehicle Motion
  • Intelligent Vehicles
  • Model Predictive Control

Project and Funding Information

  • Project ID
  • info:eu-repo/grantAgreement/EC/H2020/692455/EU/European Initiative to Enable Validation for Highly Automated Safe and Secure Systems/ENABLE-S3
  • Funding Info
  • This work has been conducted within the ENABLE-S3 project that has_x000D_ received funding from the ECSEL Joint Undertaking under Grant Agreement_x000D_ No 692455. This work was developed at Tecnalia Research & Innovation_x000D_ facilities supporting this research.

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