Efficient mixed integer programming for autonomous overtaking

Fabio Molinari; Ngoc Nguyen; Luigi Del Re

Efficient mixed integer programming for autonomous overtaking

Fabio Molinari, Ngoc Nguyen, Luigi Del Re

Institute of Design and Control of Mechatronical Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

This paper addresses the autonomous overtaking problem using model predictive control. Accordingly, a mixed integer programming approach is put forward in which the surrounding vehicles are considered as moving obstacles. Unlike existing solutions using mixed integer programming, this paper presents more efficient formulations by reducing the number of binary variables, possibly enabling to accelerate the online computation. These algorithms are illustrated via a numerical example in the accurate vehicle simulator IPG CarMaker.

Original language	English
Title of host publication	Efficient mixed integer programming for autonomous overtaking
Editors	American Control Conference 2017
Number of pages	6
Publication status	Published - May 2017

Fields of science

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

JKU Focus areas

Mechatronics and Information Processing

Cite this

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title = "Efficient mixed integer programming for autonomous overtaking",

abstract = "This paper addresses the autonomous overtaking problem using model predictive control. Accordingly, a mixed integer programming approach is put forward in which the surrounding vehicles are considered as moving obstacles. Unlike existing solutions using mixed integer programming, this paper presents more efficient formulations by reducing the number of binary variables, possibly enabling to accelerate the online computation. These algorithms are illustrated via a numerical example in the accurate vehicle simulator IPG CarMaker.",

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AB - This paper addresses the autonomous overtaking problem using model predictive control. Accordingly, a mixed integer programming approach is put forward in which the surrounding vehicles are considered as moving obstacles. Unlike existing solutions using mixed integer programming, this paper presents more efficient formulations by reducing the number of binary variables, possibly enabling to accelerate the online computation. These algorithms are illustrated via a numerical example in the accurate vehicle simulator IPG CarMaker.

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BT - Efficient mixed integer programming for autonomous overtaking

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