Title
Autonomous overtaking using stochastic model predictive control
Date Issued
07 February 2018
Access level
metadata only access
Resource Type
conference paper
Author(s)
Johannes Kepler University
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
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.
Start page
1005
End page
1010
Volume
2018-January
Language
English
OCDE Knowledge area
Ingeniería mecánica
Subjects
Scopus EID
2-s2.0-85047508481
Resource of which it is part
2017 Asian Control Conference, ASCC 2017
ISBN of the container
9781509015733
Conference
2017 11th Asian Control Conference, ASCC 2017
Sources of information:
Directorio de Producción Científica
Scopus