Wavelength sensitivity of roughness measurements using connected vehicles

ABSTRACT

Researchers previously demonstrated that a roughness index called the road impact factor (RIF) is directly proportional to the international roughness index (IRI) when measured under identical conditions. A RIF-transform converts inertial signals from connected vehicle accelerometers and speed sensors to produce RIF-indices in real time. This research examines the relative sensitivities of the RIF and the IRI to variations in dominant profile wavelengths. The findings are that both indices characterise roughness from spatial wavelengths up to 2 m with equal sensitivity. However, the RIF-transform maintains its sensitivity when characterising roughness from wavelengths beyond that. The case studies used a certified inertial profiler to collect both RIF and IRI data simultaneously from five different pavement surface types. The RIF/IRI proportionality factors distributed normally among the profiles tested. This result affirms that the RIF and IRI generally agrees. However, differences in the dominant profile wavelength among pavements will produce some spread in the degree of roughness that the indices express.

KEYWORDS:

• Connected vehicle
• inertial profiler
• intelligent transportation systems
• pavement management
• probe vehicles
• ride quality
• roughness index
• wavelength sensitivity

Acknowledgements

A grant from the Mountain Plains Consortium supported this research. The authors also express their sincere appreciation to Mr. Thomas Burchett of Fugro Roadware for his contribution in data collection at MnROAD facilities.

Additional information

Funding

The University Transportation Centre, a programme of the United States Department of Transportation, sponsored this research through its Mountain Plains Consortium (MPC) [grant number DTRT12-G-UTC08].