Evaluation of ecodriving performances and teaching method: comparing training and simple advice

Overview & Synopsis

Eco-driving style is widely known to induce up to 20% fuel consumption reduction, but little is known about differences due to different learning methods. In order to evaluate the potential impacts of future ecological driving assistance system (EDAS) in comparison with usual techniques, a statistical approach is proposed. Two kinds of experiments are analysed in this paper: In the first one, simple advice were given to the participants, while in the second one, full courses with eco-driving experts were used. Performance indicators were derived from five commonly referred golden rules of eco-driving and used as model inputs. Different kind of statistical models are discussed, among which we choose to apply the ordinary logistic regression to assess the effects of each driving advice separately. Results show that eco-driving advices are better applied after a course than just providing tips. The approach is then extended to build a generic model that can be used both to characterize and evaluate eco-driving style.