Rough roads increase vehicle operation and road maintenance costs. Consequently, transportation agencies spend a significant portion of their budgets on ride-quality characterization to forecast maintenance needs. The ...

The Road Impact Factor is a measure of ride-quality. It is derived from the average inertial response of vehicles to road roughness. Unlike the International Roughness Index, the most common measure, the road impact ...

The timely identification and localization of roadway anomalies that pose hazards to the traveling public is currently a critical but very expensive task. Hence, transportation agencies are evaluating emerging alternatives ...

Transportation agencies rely on models to predict when pavements will deteriorate to a condition or ride-index threshold that triggers maintenance actions. The accuracy and precision of such forecasts are directly proportional ...

The international roughness index is the prevalent indicator used to assess and forecast road maintenance needs. The fixed parameters of its simulation model provide the advantage of requiring relatively few traversals ...

Connected vehicles present an opportunity to monitor pavement condition continuously by analyzing data from vehicle-integrated position sensors and accelerometers. The current practice of characterizing and reporting ...

Continuous, network-wide monitoring of pavement performance will significantly reduce risks and provide an adequate volume of timely data to enable accurate maintenance forecasting. Unfortunately, transportation agencies ...

Transportation agencies rely on the accurate localization and reporting of roadway anomalies that could pose serious hazards to the traveling public. However, the cost and technical limitations of present methods ...

Methods of pavement roughness characterizations using connected vehicles are poised to scale beyond the frequency, span, and affordability of existing methods that require specially instrumented vehicles and skilled ...