Roadview Inc. Data Processsing Intern
Mandli Communications
Website
Roadview Inc. Website
Roadview Inc. Website
Roadview is an industry leader
in geospatial technologies. Since its establishment in the early 80's, the
company has continually provided inovative spatial applications that better help
us understand the world we live in today. Representing the data collection
componet of Mandli Communicaitons, Roadview specializes in the collection of
various georeferenced data from a mobile collection van. Trained in house
technicians are able to process and package the data in a variety of formats
that can be delivered to meet the unique and diverse project needs of Mandli's
large client base. Roadview is a leader
in mobile 3-D imaging and pavement data collection and has the largest fleet of
mobile LIDAR data collection vehicles in the United States.
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| 1 pavement image data frame with distress rating overlay |
Specifically, I worked within
the Pavement Management System (PMS), a division within Roadview Inc. which
focuses on accurately determining the quality of a pavement network. Networks
are assessed using various pavement distress analysis ratings. These ratings
are calculated from the Pavement Condition Index (PCI), a system developed by
the U.S. Army Corps of Engineers. The PCI used at Roadview is the industry
standard used nationwide.
The PCI calculations are derived
from the results of a visual condition survey, a process where technicians
evaluate the distress type, severity, and quantity of a particular network
(photo to the right). This distress data can be used to investigate the causes of
distress (weather,
traffic load). Using the PCI method, infrastructures are divided into segmented
inspection units which we referred to as “sample units.” The condition rating of
these sample units are applied to an entire mile long segment. By assessing
networks in this way, processing can be performed at high speeds while also
maintaining the quality and accuracy of each assessment. The photo below
shows examples of different sampling circumstances.
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| Unusual Sampling Circumstances
within the PCI |
For this example, say 100 data
frames equals a mile of actual roadway. As a technician, I would visually pan
through 100 frames and rate 10% of the data frames, choosing the 10 best sample
units within those 100 frames (based on chart below). From a visual inspection,
I deduce that about 50% of the mile segment has a similar distress type. Picking
only 10 data frames with heavy distress or 10 frames with no distress at all can
mislead clients on the actual condition rating of that particular network
segment. In this crude example, I would choose 5 frames with distress and 5
frames without, these "sample units" would accurately represent the mile being
rated. Rating network distress consists of choosing the appropriate type and
severity.
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| Criteria for pavement sampling based on the PCI |
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