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Full-Text Articles in Other Physical Sciences and Mathematics
Mapping Of Pavement Conditions Using Smartphone/Tablet Lidar Case Study: Sensor Performance Comparison, Calvin Beavers, Chad Day, Austin Krietemeyer, Scott M. Peterson, Yushin Ahn, Xiaojun Li
Mapping Of Pavement Conditions Using Smartphone/Tablet Lidar Case Study: Sensor Performance Comparison, Calvin Beavers, Chad Day, Austin Krietemeyer, Scott M. Peterson, Yushin Ahn, Xiaojun Li
Mineta Transportation Institute
Poor road conditions affect millions of drivers, and assessing the condition of paved surfaces is a critical step towards repairing them. This project explores the feasibility of using the Apple iPad Pro LiDAR sensor as a cost-effective tool for assessing the damage and condition of paved surfaces. Our research aims to provide accurate and precise measurements using readily available consumer devices and compare the results to state-of-the-art equipment. This investigation involved visual inspection, identification, and classification of pavement distresses, followed by a comparison of the iPad and iPhone LiDAR data with a survey-grade terrestrial laser scanner. The project revealed several …
Development Of The Roadway Pothole Management Program, Dingxin Cheng
Development Of The Roadway Pothole Management Program, Dingxin Cheng
Mineta Transportation Institute
Addressing the issue of potholes is a primary concern for maintaining urban infrastructure. The research team has developed a prototype pothole management program. The program includes a mobile application and two machine learning models. The mobile app enables users to upload images of potholes, report relevant information, and provide driving directions to the pothole location. With the help of this application, the user can seamlessly capture images of the potholes, record pertinent information, and submit the data for necessary action. The mobile application is an essential tool in the Pothole Management Program (PMP), as it enhances the program's efficiency, effectiveness, …
Traffic Sign Extraction From Mobile Lidar Point Cloud, Yushin Ahn, Riadh Munjy, Ziyuan Li
Traffic Sign Extraction From Mobile Lidar Point Cloud, Yushin Ahn, Riadh Munjy, Ziyuan Li
Mineta Transportation Institute
The extraction of traffic signs from Mobile Light Detection and Ranging (LiDAR) point cloud data has become a focal point in transportation research due to the increasing integration of LiDAR technologies. LiDAR, a remote sensing technology, captures detailed three-dimensional point cloud data, offering a comprehensive view of the surrounding environment. Mobile LiDAR systems mounted on vehicles enable efficient data collection, particularly for large-scale road networks. This study aims to develop and refine techniques for extracting traffic signs from Mobile LiDAR point cloud data, essential for enhancing road safety, navigation systems, and intelligent transportation solutions. By leveraging LiDAR technology, new possibilities …