A Comparative Analysis of Pavement Condition Evaluation Using Connected Vehicle Data and 3D Scanning

Abstract: The rapid proliferation of connected vehicles and the increasing availability of their generated data present a transformative opportunity for infrastructure management, particularly in pavement condition evaluation. While traditional methods, such as 3D laser scanning, have been the industry standard, connected vehicle data offers a unique perspective with potential advantages in terms of cost-effectiveness, coverage, and real-time insights.
This presentation aims to conduct a comparative analysis of pavement condition evaluation results obtained from connected vehicle data and 3D laser scanning. By examining the similarities and differences between these two methods, we seek to assess the potential of connected vehicle data as a viable alternative or complement to traditional approaches.
The study will focus on a specific geographic region and compare pavement condition assessments derived from connected vehicle data provided by a leading global crowd-sourced infrastructure data provider. This data will be contrasted with ground truth data collected through 3D laser scanning, a well-established method for capturing detailed pavement surface information.
Key aspects of the comparison will include:
* Pavement Distress Detection
* Spatial Resolution
* Cost-Effectiveness
By conducting a rigorous comparison, this presentation will provide valuable insights into the strengths and limitations of connected vehicle data for pavement condition evaluation. It will also explore the potential for integrating connected vehicle data with traditional methods to create a more comprehensive and cost-effective approach to infrastructure management.