01550544

Component

https://doi.org/10.3141/2525-07

Pavement roughness affects rolling resistance and thus vehicle fuel consumption. When a vehicle travels at constant speed on an uneven road surface, the mechanical work dissipated in the vehicle’s suspension system is compensated by vehicle engine power and results in excess fuel consumption. This dissipation depends on both road roughness and vehicle dynamic characteristics. This paper proposes, calibrates, and implements a mechanistic model for roughness-induced dissipation. The distinguishing feature of the model is its combination of a thermodynamic quantity (energy dissipation) with results from random vibration theory to identify the governing parameters that drive the excess fuel consumption caused by pavement roughness, namely, the international roughness index (IRI) and the waviness number, w (a power spectral density parameter). It is shown through sensitivity analysis that the sensitivity of model output, that is, excess fuel consumption, to the waviness number is significant and comparable to that of IRI. Thus, introducing the waviness number as a second roughness index, in addition to IRI, allows a more accurate quantification of the impact of surface characteristics on vehicle fuel consumption and the corresponding greenhouse gas emissions. This aspect is illustrated by application of the roughness–fuel consumption model to two road profiles extracted from FHWA’s Long-Term Pavement Performance database.

01592675

15-2429

English

pp 62–70

2015

Transportation Research Record: Journal of the Transportation Research Board

9780309369497

Print

Figures (9) ; References (20) ; Tables (3)

Dissipation; Fuel consumption; Mathematical models; Pavements; Power spectra; Random vibration; Rolling resistance; Roughness; Sensitivity analysis

International Roughness Index

Design; Highways; Pavements; I22: Design of Pavements, Railways and Guideways; I23: Properties of Road Surfaces

TRIS, TRB, ATRI

Dec 30 2014 12:51PM

• Adaptive Spike Removal Method for High-Speed Pavement Macrotexture Measurements by Controlling the False Discovery Rate
• Backcalculation with an Implanted Inertial Sensor
• Detecting and Correcting Localized Roughness Features
• Dynamic Viscoelastic Analysis of Falling Weight Deflectometer Deflections for Rigid and Flexible Pavements
• Evaluation and Validation of a Model for Predicting Pavement Structural Number with Rolling Wheel Deflectometer Data
• Importance of Rubber Characteristics in the Frictional Response of Asphalt Concrete Surfaces
• Measurement of Pavement Treatment Macrotexture and Its Effect on Bicycle Ride Quality
• Monitoring Pavement Surface Macrotexture and Friction: Case Study
• Peak Friction Prediction Model Based on Surface Texture Characteristics
• Performance Evaluations of Unbound Aggregate Permanent Deformation Models for Various Aggregate Physical Properties
• Study of Influence of Operating Parameters on Braking Friction and Rolling Resistance