Using truck sensors for road pavement performance investigation

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Perrotta, Federico, Parry, Tony and Neves, Luís C. (2017) Using truck sensors for road pavement performance investigation. In: ESREL 2017, 19-22 Jun 2017, Portoroz, Slovenia.

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Abstract

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 consumption of the considered truck fleet. Then, a multiple linear regression for the prediction of fuel consumption was generated. The model shows that evenness and macrotexture can impact the truck fuel consumption by up to 3% and 5%, respectively. It is a significant impact which confirms that, although the available funding for pavement maintenance is limited, the importance of limiting GHG emissions, together with the economic benefits of reducing fuel consumption are reasons to improve road condition (Zaabar & Chatti, 2010).

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/862098
Additional Information: This is an Accepted Manuscript of a book chapter published by CRC Press in ESREL-2017-Portoroz-Slovenia-18-22-June-2017 on May 25, 2017, available online: http://www.routledge.com/ESREL-2017-Portoroz-Slovenia-18-22-June-2017/Cepin-Bris/p/book/9781138629370
Keywords: Fuel Consumption, Fuel Economy, Road Conditions, Roughness, Evenness, Macro-texture, Fleet Management, Asset Management
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Civil Engineering
Related URLs:
URL
URL Type
http://esrel2017.org
UNSPECIFIED
Depositing User: Perrotta, Federico
Date Deposited: 28 Jun 2017 12:35
Last Modified: 04 May 2020 18:47
URI: https://eprints.nottingham.ac.uk/id/eprint/43787

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