Highway Departments and Airports perform regular pavement condition inspections to record cracking, rutting, smoothness, etc., which serve as important inputs into Pavement Management Systems (PMS) software. Pavement distress are analysed by PMS software in order to model deterioration and to make budget and performance-based recommendations regarding which pavements to maintain, what treatments to apply, and when to apply them.

Increasingly pavement condition data are captured using high-speed 3D lasers and high-accuracy blended inertial positioning systems. This enables fast, accurate and objective pavement assessment.

Recent advances in data integration allow these data streams to be repurposed in order to create a “Digital Twin” of multi-lane highways and airport runways. Thus expanding dataset capabilities while reducing closure time, data collection costs and staff exposure.

Digital Twin 3D models can be directly imported into Road Design Software applications and used to generate volumetric estimates, Preliminary, and Final Designs. Outputs can be sent to laser tracking total stations which can be used to control 3D pavers and milling machines.

This paper and presentation will present details of the capture technology and key workflow steps to create this dataset including: import of GPS base station data, correction to survey control, merging of multiple passes and output to LAS format. Finally, point density and accuracy of the final solution, compared to laser level and GPS Total Station, will be presented.

Access the Conference Proceedings Paper on ASCE Library 

Highway Departments and Airports perform regular pavement condition inspections to record cracking, rutting, smoothness, etc., which serve as important inputs into Pavement Management Systems (PMS) software. Pavement distress are analysed by PMS software in order to model deterioration and to make budget and performance-based recommendations regarding which pavements to maintain, what treatments to apply, and when to apply them.

Increasingly pavement condition data are captured using high-speed 3D lasers and high-accuracy blended inertial positioning systems. This enables fast, accurate and objective pavement assessment.

Recent advances in data integration allow these data streams to be repurposed in order to create a “Digital Twin” of multi-lane highways and airport runways. Thus expanding dataset capabilities while reducing closure time, data collection costs and staff exposure.

Digital Twin 3D models can be directly imported into Road Design Software applications and used to generate volumetric estimates, Preliminary, and Final Designs. Outputs can be sent to laser tracking total stations which can be used to control 3D pavers and milling machines.

This paper and presentation will present details of the capture technology and key workflow steps to create this dataset including: import of GPS base station data, correction to survey control, merging of multiple passes and output to LAS format. Finally, point density and accuracy of the final solution, compared to laser level and GPS Total Station, will be presented.

**[Access the Conference Proceedings Paper on ASCE Library](https://ascelibrary.org/doi/10.1061/9780784483527.016)** 

Using 3D Pavement Surveys to Create a Digital Twin of Your Runway or Highway

Welcome to the International Airfield and Highway Pavements Conference of the Transportation & Development Institute (T&DI) of ASCE. This international conference will provide an unrivaled chance to interact and exchange information with worldwide leaders in the fields of highway and airport pavements, as well as airport safety technologies.

This conference will bring together designers, project/construction managers, academics, and contractors from around the world to discuss the state-of-the-art implementation, construction, design, in airfield and highway pavements.

Paper Proceedings: https://doi.org/10.1061/9780784483527 | https://doi.org/10.1061/9780784483503 | https://doi.org/10.1061/9780784483510

Conference DOI: https://doi.org/10.26226/m.63284d15cb3e8e0012755dd4