Semester of Graduation
Master of Civil Engineering (MCE)
Department of Civil & Environmental Engineering
One of the fundamental sources of data for traffic analysis is vehicle counts, which can be conducted either by the traditional manual method or by automated means. Different agencies have guidelines for manual counting, but they are typically prepared for particular conditions. In the case of automated counting, different methods have been applied, but You Only Look Once (YOLO), a recently developed object detection model, presents new potential in automated vehicle counting. The first objective of this study was to formulate general guidelines for manual counting based on experience gained in the field. Another goal of this study was to develop a computer program for vehicle counting from pre-recorded video applying the YOLO model. The documented general guidelines provided in this project can be useful in acquiring the required standard and minimizing the cost of a manual counting project. The accuracy of the automated counting program was found to be about 90 percent for total daily counts, although most of that error was a consistent undercounting by automated counting.
Majumder, Mishuk, "An Approach to Counting Vehicles from Pre-Recorded Video Using Computer Algorithms" (2020). LSU Master's Theses. 5231.
Dr. Chester G Wilmot