Gravel roads are low cost roads mainly located in rural areas that experiences seasonal variations in traffic volumes with significantly higher flows occurring around harvest time. This novel study researches the use of the Unmanned Aerial Vehicle (UAV) as a road data collection platform, to identify and quantify road condition parameters. The study took place in three test sections in Brookings, South Dakota. Physical measurements of road features were taken to establish the existing road condition of the test sections using the Field Measurement method. The UAV attached with image acquisition system was flown over the test sections. Similar road features were measured from UAV acquired images using image processing software (UAV method). The average values of the feature measurements from both the methods were compared. The result reveals the average accuracy of the UAV method is 12.4% in comparison to the Field Measurement method. This makes the UAV method a unique alternative to the Field Measurement method as the current method is laborious and affected by operator efficiency.
|School||SOUTH DAKOTA STATE UNIVERSITY|
|Subjects||Civil engineering; Remote sensing|
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