If you are a road condition data collection enthusiast AND a professional leaf-peeper, this post is for you! (We are really reaching here, but we know there are a few of you out there!)
We set up a good, old-fashioned experiment to test how leaves affect road condition data collection. Our field crew collected a specific street three times – first with no leaves, and twice after leaves had been thrown onto a portion of the road. Our test section of road was divided into:
Section A: 0-77 ft No leaves.
Section B: 77-110 ft Few leaves.
Section C: 110-200 ft Many leaves.
Section D: 200-250 ft Few leaves.
We compared the measurements of IRI, rutting, texture, raveling, and cracking between the runs. The following graphs show the effect of leaves on various deliverables. For example, with leaves, erroneous rut depths of over 3 cm (1.2 in) are detected. Lanes are also not detected correctly as can be seen in the images above. Note that since the reporting interval is very short (5 ft), repeatability for the areas without leaves is as expected.
So, how should a data collection provider filter out invalid data from these results prior to importing into a PMS?
ICC and IMS have two ways to catch this in our process that focus on precise measurement and effortless monitoring:
- The field crew has a debris/leaves event key they hit whenever they see debris in the road. Debris could include sand, dirt, leaves, etc.
- At the QA/QC stage, we perform a visual review of the automatically-rated distresses where we are looking for anomalous data that could indicate debris in the road.
Our data collection operators are trained to detect these (and many other!) situations and know when to exclude invalid data from reports. This is just another example of how ICC and IMS measure with confidence and monitor with ease.
Is your community currently buried in leaves but in desperate need of a road condition survey? Contact us today! We’d love to help you formulate a plan of action before everything freezes over.