The transformative power of mobile mapping for transportation infrastructure

Point cloud and 360-degree image collected with the Leica Pegasus: Two Ultimate. (Photo: Leica Geosystems )

The latest mobile mapping innovations are transforming how we manage, design and monitor our critical infrastructure — in particular, reshaping road maintenance. Through the advance of mobile mapping and reality capture imagery, our ability to map, proactively survey and even design roads, from simulating the vibration of a vehicle on a road to mapping out city routes, is drastically improving through the symbiosis of the digital and physical worlds.

Leveraging data: Traditional vs autonomous mapping
Traditional methods for assessing damage to road surfaces are highly manual, field-based, labor-intensive and time-consuming. Visual inspection, for example, comes with resourcing challenges, data exhaustivity and inaccurate assessments, making quality assessment and control a challenge. There is limited accurate analysis of how the road changes over time, and the work involves significant safety issues, with surveyors required to work in the field near live traffic and often requiring the traffic to be interrupted to allow measurements to be taken.
By contrast, automated laser scanning solutions provide spatial geometry for precise measurements that imagery-only methods cannot capture when assessing damage to road surfaces. They overcome any inaccuracies or lack of detail regarding location and circumstances. This technology also allows professionals to study the surrounding context of the road and measure the depth of a hole or the size of a crack with spatial data, which visual methods cannot capture. Hexagon’s mobile mapping systems, used for virtual road management and maintenance, enable access to a completely virtual environment to unlock the insights this data provides, transforming how we manage our infrastructures. With spatial data collected over time, asset degradation and other factors foundational to maintaining road infrastructure can be predicted by the more effective leveraging of data.

With geospatial data allowing the accurate mapping of potholes, rutting and depressions alongside accurate location mapping using GIS, asset managers can map the data onto real-world imagery to create an interactive, 3D model integrating the physical world and geospatial data. Combined, this unlocks insights and overhauls efficiency for asset managers performing road maintenance, allowing them to prioritize and make decisions based on data live in the field.

Veris deploys Hexagon’s solutions for road mapping
Recently, Hexagon’s technology was used by Veris, a provider of spatial data services to deliver end-to-end solutions for road management and maintenance in Australia. It combined a Leica Geosystems mobile mapping system, the Leica Pegasus:Two Ultimate, with Hexagon M.App Enterprise to create a high-quality, configurable solution and designed its own bespoke software platform RoadSiDe.
Veris used the mobile mapping system on the Hume and Melba Highways to identify and assess road defects and ground penetrating radar (GPR) to rapidly perform data capture of the road corridor. Then, RoadSiDe analytics and machine learning enabled the delivery of the data and insights using M.App Enterprise and Luciad Fusion, integrating 3D visualizations and 2D dashboards to identify, assess and quantify the road condition as part of the only full 3D road condition and corridor platform. The in-house solution for scripts and automation Veris developed made it simple for their clients to visualize and interact with the data, providing analytics and value-added services on demand that offered valuable insights for its clients.

As part of the surface defects workflow they use for analysis, Veris takes the raw point cloud data and compares it with the ideal road exterior to create a surface difference model, followed by contours and improved defect definition. This cross-comparison and integration allows them to use and visualize the data they acquired by precisely measuring the gaps and holes. Veris efficiently captured road cracking in detail with its additional 12MP/20MP camera system. These are then mapped into the RoadSiDe dashboard, and cracking width and length are captured within the geodatabase. Machine learning is used to detect cracks in the road surface before pixels are classified into clusters and projected onto the original images for verification and quality assurance. This can then be integrated with location coordinates, allowing clients to see precisely where each cracking is located. With this georeferenced data digitized and visualized, Veris can leverage as much of its data as possible into the most effective platform for its users.

Expanding the scope of mobile mapping
The data captured by mobile mapping solutions is just as helpful in designing roads as in maintaining them and can be incorporated into the construction of future roads and city planning. The data even can be used to simulate, for example, the movement of a heavy truck through city streets to examine whether it will impact potholes or damage any road signs, allowing asset managers to predict and prevent damage and maintain road infrastructure for years to come.