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All Outputs (7)

Comparison of truck fuel consumption measurements with results of existing models and implications for road pavement LCA (2018)
Conference Proceeding
Perrotta, F., Parry, T., Neves, L. C., Buckland, T., Benbow, E., & Viner, H. (2018). Comparison of truck fuel consumption measurements with results of existing models and implications for road pavement LCA.

Life Cycle Assessment (LCA) is increasingly used to evaluate the impact of all lifecycle phases of road pavements on the environment. From the late ‘90s, this technique has continuously evolved and improved, however, there are still limitations and u... Read More about Comparison of truck fuel consumption measurements with results of existing models and implications for road pavement LCA.

A machine learning approach for the estimation of fuel consumption related to road pavement rolling resistance for large fleets of trucks (2018)
Conference Proceeding
Perrotta, F., Parry, T., Neves, L. C., & Mesgarpour, M. (2018). A machine learning approach for the estimation of fuel consumption related to road pavement rolling resistance for large fleets of trucks.

There remains a level of uncertainty concerning the methodological assumptions and parameters to consider in the estimation of road vehicle fuel consumption due to the condition of road pavements. In fact, recent studies highlighted how existing mode... Read More about A machine learning approach for the estimation of fuel consumption related to road pavement rolling resistance for large fleets of trucks.

A big data approach for investigating the performance of road infrastructure (2018)
Conference Proceeding
Perrotta, F., Parry, T., Neves, L. C., Mesgarpour, M., Benbow, E., & Viner, H. (2018). A big data approach for investigating the performance of road infrastructure. In n/a

“Using truck sensors for road pavement performance investigation” is a research project within TRUSS, an innovative training network funded from the EU under the Horizon 2020 programme. The project aims at assessing the impact of the condition of the... Read More about A big data approach for investigating the performance of road infrastructure.

Application of machine learning for fuel consumption modelling of trucks (2017)
Conference Proceeding
Perrotta, F., Parry, T., & Neves, L. C. (2017). Application of machine learning for fuel consumption modelling of trucks.

This paper presents the application of three Machine Learning techniques to fuel consumption modelling of articulated trucks for a large dataset. In particular, Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN) mod... Read More about Application of machine learning for fuel consumption modelling of trucks.

Using truck sensors for road pavement performance investigation (2017)
Conference Proceeding
Perrotta, F., Parry, T., & Neves, L. C. (2017). Using truck sensors for road pavement performance investigation.

Considering data from 260 articulated trucks, with ~12900 cc Euro 6 engines driving along a motorway in England (M18), the study first shows how different approaches lead to the conclusion that road pavement surface conditions influence fuel consumpt... Read More about Using truck sensors for road pavement performance investigation.

Route level analysis of road pavement surface condition and truck fleet fuel consumption (2017)
Conference Proceeding
Perrotta, F., Trupia, L., Parry, T., & Neves, L. C. (2017). Route level analysis of road pavement surface condition and truck fleet fuel consumption.

Experimental studies have estimated the impact of road surface conditions on vehicle fuel consumption to be up to 5% (Beuving et al., 2004). Similar results have been published by Zaabar and Chatti (2010). However, this was established testing a limi... Read More about Route level analysis of road pavement surface condition and truck fleet fuel consumption.

A big data approach to assess the influence of road pavement condition on truck fleet fuel consumption (2017)
Conference Proceeding
Perrotta, F., Parry, T., & Neves, L. C. (2017). A big data approach to assess the influence of road pavement condition on truck fleet fuel consumption.

In Europe, the road network is the most extensive and valuable infrastructure asset. In England, for example, its value has been estimated at around £344 billion and every year the government spends approximately £4 billion on highway maintenance (Ho... Read More about A big data approach to assess the influence of road pavement condition on truck fleet fuel consumption.