# Attention Horizon as a Predictor for the Fuel Consumption Rate of Drivers
## 2 Materials and Methods
### Extraction of Red Light-Approaching Trajectories
In addition to that, metrics such as the one presented in this paper can be combined with other similar metrics, quantifying driver behavior to create a better driver ranking algorithm. It is important that each of those metrics is as unbiased as possible, and that they have a clear correlation with a desired outcome, e.g., lower fuel consumption, in the case of this paper. Future work can also include developing more of these metrics, capturing other aspects important to driver ranking as well as investigating ways to combine these metrics into a fair driver score. Conceptualization, S.N., R.P. and H.S. ; methodology, H.S., S.N. and R.P. ; software, validation, formal analysis, and investigation, H.S. ; resources, R.P. and M.S. ; data curation, H.S. ; writing--original draft preparation, H.S., S.N., R.P. and M.S. ; writing--review and editing, H.S. and M.S. ; visualization, H.S. ; supervision, S.N., R.P. and M.S. All authors have read and agreed to the published version of the manuscript. This work was partially supported by a Eurostars grant E!114213 Battery Cortex. Not applicable. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. ## Abbreviations

The following abbreviations are used in this manuscript: \begin{tabular}{l l} AH & Attention horizon \\ FCR & Fuel consumption rate \\ CAN & Communication area network \\ GPS & Global Positioning System \\ \end{tabular} 

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