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Driving Style Recognition for Co-operative Driving: A Survey

Authors:
Anastasia Bolovinou
Angelos Amditis
Francesco Bellotti
Mikko Tarkiainen

Keywords: driving behaviour; vehicle dynamics; time-series analysis; supervised learning; classification; co-operative system

Abstract:
This paper serves as a critical survey for automatic driving style recognition approaches and presents “work in progress” ideas that can be used for the development of intelligent context-adaptive driving assistance applications. Furthermore, a preliminary specification of a context-adaptive application that can be described by the following three steps is provided: at first, driving style is automatically classified into one out of a set of predefined classes that are learnt through historic driving and trip data; secondly, based on the driving style recognition a context-adaptive driving application is proposed; thirdly, eco-safe and co-operative driving behaviour can be rewarded by the system by introducing a serious game theoretic approach. While the focus of this paper lies on reviewing the state of the art for implementing the first step, providing the high-level specification of the two other steps offers valuable insight on the requirements of such collaborative driving application.

Pages: 73 to 78

Copyright: Copyright (c) IARIA, 2014

Publication date: May 25, 2014

Published in: conference

ISSN: 2308-4146

ISBN: 978-1-61208-341-4

Location: Venice, Italy

Dates: from May 25, 2014 to May 29, 2014