@inproceedings { , title = {Route level analysis of road pavement surface condition and truck fleet fuel consumption}, abstract = {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 limited number of vehicles under carefully controlled conditions including, for example, steady speed or coast down and no gradient, amongst others. This paper describes a new “Big Data” approach to validate these estimates at truck fleet and route level, for a motorway in the UK. Modern trucks are fitted with many sensors, used to inform truck fleet managers about vehicle operation including fuel consumption. The same measurements together with data regarding pavement conditions can be used to assess the impact of road surface conditions on fuel economy. They are field data collected for thousands of trucks every day, year on year, across the entire network in the UK. This paper describes the data analysis developed and the initial results on the impact of road surface condition on fuel consumption for journeys of 157 trucks over 42.6km of motorway, over a time period of one year. Validation of the relationship between road pavement surface condition and vehicle fuel consumption will increase confidence in results of LCA analyses including the use phase.}, conference = {Pavement Life-Cycle Assessment Symposium 2017}, note = { School:Eng3,}, organization = {Champaign, Illinois (USA)}, publicationstatus = {Published}, url = {https://nottingham-repository.worktribe.com/output/855515}, keyword = {Pavement LCA, Pavement Conditions, Fuel Consumption, Road Asset Management}, year = {2017}, author = {Perrotta, Federico and Trupia, Laura and Parry, Tony and Neves, Lus C.} }