Date of Award
8-2018
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Civil Engineering
Committee Member
Dr. Wayne A. Sarasua, Committee Chair
Committee Member
Dr. William J. Davis
Committee Member
Dr. Jennifer H. Ogle
Committee Member
Dr. Christopher Post
Committee Member
Dr. Bradley J. Putman
Abstract
Ensuring adequate pavement cross slope on highways can improve driver safety by reducing the potential for water sheeting and ponding. Collecting cross slope data is typically only based on small sample because efficient technology and means to collect accurate cross slope data has been evasive. The advent of Light Detection and Ranging (LiDAR) scanning technology has proven to be a valuable tool in the creation of 3D terrain models. Combined with other technologies such as Global Positioning Systems (GPS) and Inertial Measurement Unit devices (IMU) it is now possible to collect accurate 3D coordinate data in the form of a point cloud while the data collection system is moving. This study provides an evaluation of both Airborne LiDAR Scanning (ALS) and Mobile Terrestrial LiDAR Scanning (MTLS) systems regarding the accuracy and precision of collected cross slope data and documentation of procedures needed to calibrate, collect, and process this data.
ALS data was collected by a single vendor on a section of freeway in Spartanburg, South Carolina and MTLS data was collected by six vendors on four roadway sections in South Carolina. The MTLS cross slopes were measured on 23 test stations using conventional surveying methods and compared with the LiDAR-extracted cross slopes. Results indicate that both adjusted and unadjusted MTLS derived cross slopes meets suggested cross slope accuracies (±0.2%). Unadjusted LiDAR data did incorporate corrections from an integrated inertial measurement unit, and high accuracy real-time kinematic GPS, however, was not post-processed adjusted with ground control points.
Similarly, airborne LiDAR-extracted cross slopes was compared with conventional surveying measurement on five test stations along the freeway study section. Whereas, the ALS data accuracy was over the minimum acceptable error when two sides of the travel lanes were used to estimate the cross slope, the use of a fitted line to derive the cross slope provided accuracies similar to the MTLS systems.
The levels of accuracy demonstrate that MTLS and ALS can be reliable methods for cross slope verification. Adoption of LiDAR would enable South Carolina Department of Transportation (SCDOT) or other highway agencies to proactively address cross slope and drainage issues.
When rain falls on a pavement surface, the water depth that accumulates can result in hydroplaning. Previous research has not clearly defined a water depth at which hydroplaning occurs; however, there is considerable agreement that a water depth equal to 0.06 inches as the acceptable upper limit of water depth to minimize the possibility of hydroplaning. This research also explored the potential for hydroplaning with regard to the range of vehicle speed, tire tread depth, tire pressure, and pavement surface texture. Using the results of the sensitivity analysis to provide roadway context combined with MTLS derived cross slope data, SCDOT and other highway agencies can use a data driven approach to evaluate cross slopes and road segments that need corrective measures to minimize hydroplaning potential and enhance safety.
Recommended Citation
Shams Esfandabadi, Alireza, "Highway Cross Slope Measurement Using Airborne and Mobile LiDAR" (2018). All Dissertations. 2759.
https://tigerprints.clemson.edu/all_dissertations/2759