Uses and Challenges of Collecting LiDAR Data from a Growing Autonomous Vehicle Fleet: Implications for Infrastructure Planning and Inspection Practices
The use of Light Detection and Ranging (LiDAR) technology has been growing in the transportation industry in recent years. The technology has been proven to provide precise, accurate, and high-density point clouds that can be related to a global reference frame (El-Sheimy et al., 2005; Shan and Toth, 2009). Extensive research in the area has shown how this technology can be used for anything from construction quality control to safety assessments to infrastructure management (e.g. Yu et al., 2015; Riviero et al., 2016; Pu et al., 2011; Geiger et al., 2012; Lato et al., 2012; He et al., 2017, Neupane et al., 2018; Rister et al., 2018). Of particular interest for this project proposal is how transportation agencies can utilize the Big Data that will result from a growing fleet of autonomous vehicles. Agencies have had experience with Big Data in the past (Zhao et al., 2018). However, the Big Data of autonomous vehicles is likely to be of unprecedented magnitude (e.g. Matthews, 2018; Marr, 2017; Clerkin, 2017). How will agencies handle such a data set, should they choose to collect it? How much data can agencies expect from a variety of different scenarios? Will they need to filter the data they receive? How many uses can they get out of these data? This proposed project will help agencies answer some of those questions.
Language
- English
Project
- Status: Active
- Funding: $99985
-
Contract Numbers:
69A3551747108
-
Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
North Dakota State University
P.O. Box 6050, Department 2880
Fargo, ND United States 58108-6050 -
Project Managers:
Kline, Robin
-
Performing Organizations:
Civil and Environmental Engineering Department
Logan, UT United States -
Principal Investigators:
Mekker, Michelle
- Start Date: 20181018
- Expected Completion Date: 20220731
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Source Data: MPC-577
Subject/Index Terms
- TRT Terms: Data collection; Data files; Intelligent vehicles; Laser radar; Vehicle fleets
- Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01683974
- Record Type: Research project
- Source Agency: Mountain-Plains Consortium
- Contract Numbers: 69A3551747108
- Files: UTC, RiP
- Created Date: Oct 22 2018 10:42AM