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Project Details

Title:Uses and Challenges of Collecting LiDAR Data from a Growing Autonomous Vehicle Fleet: Implications for Infrastructure Planning and Inspection Practices
Principal Investigators:Michelle Mekker
University:Utah State University
Project #:MPC-577
RiP #:01683974
Keywords:data collection, data files, intelligent vehicles, laser radar, vehicle fleets


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.

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