Autonomous overtaking using stochastic model predictive control

  • Patrick Schrangl (Speaker)

Activity: Talk or presentationContributed talkscience-to-science

Description

This paper presents a control algorithm for autonomous overtaking problem using stochastic model predictive control. This algorithm relies on suitable prediction for the longitudinal and lateral speeds of the surrounding vehicles. Accordingly, these information are used to formulate suitable dynamics constraints for the proposed control algorithm which determines the need of overtaking action by tracking a suitable longitudinal speed reference and a lateral position reference,while avoiding the obstacles. Finally, the efficiency of the proposed algorithm is illustrated by two traffic scenarios in the environment of the reliable traffic simulator IPG CarMaker.
Period19 Dec 2017
Event titleThe 2017 Asian Control Conference – ASCC 2017
Event typeConference
LocationAustraliaShow on map

Fields of science

  • 207109 Pollutant emission
  • 202027 Mechatronics
  • 206001 Biomedical engineering
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202034 Control engineering
  • 206002 Electro-medical engineering
  • 203027 Internal combustion engines

JKU Focus areas

  • Mechatronics and Information Processing