
handle: 11567/780610
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.
classification, vehicle dynamics, time-series analysis, supervised learning, co-operative system, driving behaviour
classification, vehicle dynamics, time-series analysis, supervised learning, co-operative system, driving behaviour
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