Formal characterization of an efficient driving evaluation process for companies of the transport sector

Public institutions and private companies all around the world agree that road transport is one of the main sectors responsible for global warming. With this in mind, all of them have designed actions to increase efficiency and reduce fuel consumption and emissions. A favorite for the companies is eco-driving because it can improve the fleet performance without a great investment. However, although these programs have achieved promising results in the majority of the experiences, the figures are not so encouraging in the long term. In many cases this decrease is produced by fuzzy reward programs or the total lack of them. Nevertheless, any coherent reward program, in order to be effective, must be associated with a complete and fair evaluation process which takes into account all the different aspects and complexities related with driving. In this paper, we propose a formal characterization of an efficient driving evaluation process which starts with a review of many different driving recommendation systems. These recommendations are used as seeds to build a set of formal competences that any eco driver must have, as well as the learning outcomes associated with each competence. A set of patterns of driving behaviors are defined, that allow confirming any of the learning outcomes. The definition also comprises a set of Key Performance Indicators (KPIs) for each learning outcome. These KPIs allow measuring the progress associated with each competence. Finally, we also propose some relevant differences that must be taken into account for the goals associated with each KPI, depending on the domain of application: type and road geometry, vehicle type (automatic or manual, passengers, cargo or not, public or private), amount of traffic, weather. Some examples of this driver characterization have been included to demonstrate the process.