01592017

Component

https://doi.org/10.3141/2589-13

The United States relies on the performance of more than 4 million miles of roadways to sustain its economic growth and to support the dynamic mobility needs of its growing population. The funding gap to build and maintain roadways is ever widening. Hence the continuous deterioration of roads from weathering and usage poses significant challenges. Transportation agencies measure ride quality as the primary indicator of roadway performance. The international roughness index is the prevalent measure of ride quality that agencies use to assess and forecast maintenance needs. Most jurisdictions use a laser-based inertial profiler to produce the index. However, technical, practical, and budget constraints preclude that use for some facility types, particularly local and unpaved roads that make up more than 90% of the road network in the United States. This study expands on previous work that developed a method to transform sensor data from many connected vehicles to characterize ride quality continuously, for all facility types and at any speed. The case studies used a certified and calibrated inertial profiler to produce the international roughness index. A smartphone aboard the inertial profiler produced simultaneously the roughness index of the connected vehicle method. The results validate the direct proportionality relationship between the inertial profiler and connected vehicle methods within a margin of error that diminished below 5% and 2% after 30 and 80 traversal samples, respectively.

01589874

16-0525

English

pp 119–126

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309369916

Print

Figures (5) ; References (26) ; Tables (4)

Case studies; Connected vehicles; Information processing; Mobile communication systems; Probe vehicles; Ride quality; Roughness; Smartphones

International Roughness Index

United States

Data and Information Technology; Design; Environment; Highways; Maintenance and Preservation; Pavements

TRIS, TRB, ATRI

Jan 12 2016 4:22PM

• Computational Technique for Detecting Errors in Network-Level Pavement Condition Data
• Developing a Correlation Between the Pavement Condition Ratings Used by Five Federal Lands Management Agencies
• Evaluating Needs of Road Maintenance in Sweden with the Mixed Proportional Hazards Model
• Global Procedure for Temperature Adjustment of Measured Pavement Deflection Data: Based on the Long-Term Pavement Performance Seasonal Monitoring Program
• Hybrid Modeling Approach for Quantifying Maintenance and Rehabilitation Treatment Effectiveness of Asphalt Pavements
• Imperfect Preventive Maintenance Strategy for Flexible Pavements Based on Threshold Reliability, Cost Optimization, and Mechanistic–Empirical Analysis
• Influence of Pavement Condition Data Variability on Network-Level Maintenance Decision
• Informing Roadway Sustainability Practices by Using Greenroads Certified Project Data
• Methodology for Determining Performance Life of Hot-Mix Asphalt Mixtures
• Model Development, Field Section Characterization, and Model Comparison for Excess Vehicle Fuel Use Attributed to Pavement Structural Response
• Prediction of Pavement Performance: Application of Support Vector Regression with Different Kernels
• Rational Procedure for Determination of Rut Depth Intervention Level in Network-Level Pavement Management
• Road Section Length Variability on Pavement Management Decision Making for Ontario, Canada, Highway Systems
• Seed-Based Approach for Automated Crack Detection from Pavement Images
• Three-Stage Least Squares Analysis of Postrehabilitation Pavement Performance
• Use of Three-Dimensional Pavement Surface Data to Analyze Crack Deterioration: Pilot Study on Georgia State Route 26
• Validation of Dynamic Simulation of Slow-Moving Surface Deflection Measurements