Roughness measurements are advancing road research

By Brett Lambden

Within our lab in Saskatoon, Canada, most of the wall décor within the materials lab is safety signage and hazard identification, but beyond the equipment I.D.s, stuck upon the walls are also different asphalt stickers. This one in particular “Asphalt – The Smooth Ride” – which has survived a couple of life cycles in the lab – is in fact a quantifiably true statement.

The international roughness index (IRI) measurements of asphalt roads are significantly better than that of concrete. Asphalt roads are the arteries of modern transportation systems, facilitating the seamless movement of people and goods with the best driving experience. Improving the longevity and performance of these crucial infrastructures requires continuous research and innovation.

One key input available for asset owners, maintenance planners, and material engineers involves the measurement of IRI, a parameter that provides insights into road surface ride quality. In recent years, advancements in technology have enabled engineers to obtain precise IRI measurements through a database of seasonal road scans. This information is now being applied to advance asphalt road research.

Understanding IRI measurements

The international roughness index serves as a recognized measurement for evaluating the quality of road surfaces. It quantifies the vertical deviations of a road profile from a straight line, offering a numerical representation of the road’s roughness. Traditionally, IRI measurements were obtained using specialized equipment mounted on vehicles that physically traversed the road. However, the advent of advanced scanning technologies has ushered in a new era, allowing for non-invasive, high-resolution IRI measurements.

Modern road scans now utilize LiDAR (Light Detection and Ranging) and high-resolution cameras to capture detailed 3D images of road surfaces. These scans provide a wealth of data, including the precise elevation of road points, allowing for accurate IRI calculations. Engineers can now have more data to obtain comprehensive information about the road’s condition and can access historical performance to maintenance applications and rehabilitations in order to apply the right treatment at the right time.

In discussing these advancements with Dr. Martin Jasso, Bituminous Materials Chair at the University of Calgary, a few areas of interest were discussed where better IRI measurements can be applied to asphalt road research:

1. Performance Evaluation
IRI roughness measurements play a role in evaluating the performance of asphalt roads. By analyzing the data over time, engineers can assess the impact of various factors such as weather, traffic load and maintenance practices on road roughness. This information is invaluable for designing more durable and structurally resilient asphalt mixes that can withstand the challenges of the environment in which they are placed.

2. Predictive Maintenance
Road scans and IRI measurements enable engineers to predict and schedule maintenance activities more effectively. By identifying sections of the road with deteriorating conditions, preventive measures can be implemented to address issues before they escalate, extending the lifespan of the asphalt and reducing overall maintenance costs.

3. Material Science Developments

IRI measurements obtained from roads provide a wealth of data for materials scientists. This data aids in developing advanced materials that exhibit superior durability and resistance to wear, ultimately leading to longer-lasting and more sustainable asphalt road surfaces.

4. Optimizing Design
A detailed database over time allows engineers to refine and optimize road design parameters. This includes adjusting asphalt mix compositions, pavement thickness, and other structural elements to enhance the overall smoothness and improved experience on the road.

Future direction

Complimentary to LiDAR, an implementation of fully automatized IRI scanning by drones could provide fast and reliable information. The utilization of guided graphical evaluation combined with machine learning algorithms could provide real-time insights into the complex interactions between road conditions and various influencing factors to the smooth ride level, including structural and environmental. Additional data sets could be incorporated such as other DOTs databases. The development of real-time monitoring systems can offer immediate feedback on road performance after different environmental events, allowing for rapid response to emerging issues to increase life cycle. As cameras continue to improve, micro-cracks and other signs of initial deterioration that haven’t affected IRI measurements yet could also be captured and logged.

In conclusion, utilizing accurate IRI roughness measurements represents an opportunity forward in asphalt road research. By using these advancements in timely measurement and observation we can keep asphalt leading the way in construction as the smooth ride.

Lambden is a Technical Services & Innovation Manager for Cenovus Energy based in Saskatoon, Canada.