Using truck sensors for road pavement performance investigation

Perrotta, Federico; Parry, Tony; Neves, Lu�s C.

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).

Citation

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

• Conference Name: ESREL 2017
• End Date: Jun 22, 2017
• Acceptance Date: Feb 2, 2017
• Publication Date: May 25, 2017
• Deposit Date: Jun 28, 2017
• Publicly Available Date: May 26, 2018
• Peer Reviewed: Peer Reviewed
• Keywords: Fuel Consumption, Fuel Economy, Road Conditions, Roughness, Evenness, Macro-texture, Fleet Management, Asset Management
• Public URL: https://nottingham-repository.worktribe.com/output/862098
• Publisher URL: https://www.crcpress.com/ESREL-2017-Portoroz-Slovenia-18-22-June-2017/Cepin-Bris/p/book/9781138629370
• Related Public URLs: http://esrel2017.org
• 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