Multivariate and location-specific correlates of fuel consumption: A test track study

Timo Melman*, David Abbink, Xavier Mouton, Adriana Tapus, Joost de Winter

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
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Current predictors of fuel consumption are typically based on computer simulations or data collections in real traffic, where the route and vehicle type are not under the researcher's control. Here, we predicted fuel consumption using test track data, an approach that allowed for location-specific predictions. Ninety-one drivers drove a total of 4617 laps, in two vehicles (Renault Mégane, Renault Clio), on two routes (highway and mountain), and with two eco-driving instructions (normal and eco). A multivariate analysis at the level of laps showed a strong predictive value for metrics related to speed, RPM, and throttle position, but with a considerable amount of variance attributable to route and vehicle type. A subsequent location-specific analysis showed that the predictive correlation of driving speed and throttle position fluctuated strongly during the lap and at some locations even became negative. We conclude that there is considerable potential in instantaneous location-specific prediction of fuel consumption.

Original languageEnglish
Article number102627
Number of pages17
JournalTransportation Research Part D: Transport and Environment
Publication statusPublished - 2021


  • CAN-bus data
  • Driving metrics
  • Eco-driving
  • Principal component analysis (PCA)
  • Test track

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