Using statistical models to characterize eco-driving style with an aggregated indicator

This paper presents the construction of an aggregated indicator of a fuel-efficient driving style, in order to construct an efficient Ecological Driving Assistance System (EDAS). Such an eco-index can be used to detect eco-driving behaviour, but also to give to the driver useful advices to help him improving his driving efficiency without deteriorating safety. The logistic regression is used to model our experimental dataset of twenty subjects driving twice the same route: normally or following the golden rules of eco-driving. Depending on some driving indicators, the estimated probability of being an eco-driver is used as an eco-index to characterize that driving pattern. This work show how such a simple aggregated indicator, related to driving dynamics rather than fuel consumption, can be useful for driver monitoring and information. Two models, from the simplest to the most complicated, are compared, and their performances analysed.