Revolutionary Diagnostic Tool Incorporates LiDAR and Elevation Data for Greater Insights
There is an old saying that “the squeaky wheel gets the grease.” This could mean, for example, that the person who complains the loudest will be the one who is heard (and whose complaint is subsequently addressed). Should those in charge always act based on the complaints that reach them most successfully?
When prioritizing roadway safety projects, in contrast, most would agree that this process should be based on empirical data rather than on the loudest complaints. For example, intersections or road segments identified as being more hazardous based on such factors as pavement conditions and crash data should typically be given priority over those identified as being less hazardous. Suppose you agree that this type of data should be used to help rank road safety projects. Even so, once a problem is ready to be addressed, what can help safety engineers to select the right countermeasure that will fix the roadway?
Limitations of Traditional Safety Diagnoses
Across North America, government guidelines require Departments of Transportation and other transportation agencies to make data-driven decisions for prioritizing road safety projects with the goals of reducing accidents, fatalities, and serious injuries. In general, road improvement projects are prioritized based on problematic road locations that are analyzed by using both historical and up-to-date crash data, as well as by including other factors such as road conditions, average daily traffic, and so forth.
However, having reliable data that places the greatest “at-risk” sections of roadway at the top of the priority list is only part of the solution. Equally important, the diagnosis tools must also be effective, but traditionally, they have been limited. Techniques such as traditional GIS tools and maps, linear graphs, charts, and even video logs do not offer a 3D perspective. A three-dimensional perspective allows safety engineers to have a holistic understanding of locations that have been identified through network screening or crash investigations.
Enter the 3D Digital Reality Diagnosis
What is a 3D Digital Reality Diagnosis? This method lets safety professionals analyze an at-risk location in 3D. It does this by assimilating non-traditional sources of data in the diagnosis process. These can consist of data such as Digital Elevation Models, Imagery, Mobile/terrestrial LiDAR, Airborne LiDAR, and even 3D CAD files.
With seamless integration of these 3D data sources, you get a more realistic view of the contributing factors at the problematic location. A better view of reality helps safety engineers more accurately assess what the contributing factors are in order to select the most cost-effective countermeasures.
The result? Measurable progress toward reduction of fatalities and serious injuries on state and local highways.
For a deeper dive into the process, take a look at the webinar, “Leveraging 3D Digital Reality to Augment the Diagnosis Process for Roadway Safety Management.”