United States Department of Transportation
i
High-Resolution Micro Traffic Data From Roadside LiDAR Sensors for Connected-Vehicles and New Traffic Applications
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2018-10-01
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[PDF-3.13 MB]
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Edition:Final report
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Abstract:This report documents and presents algorithms and procedure developed for extracting high-accuracy high-resolution trajectory data from roadside LiDAR sensors. The developed methods were evaluated with data from various traffic scenarios. Pilot applications of roadside LiDAR trajectory data for pedestrian-crossing-road prediction, animal-crossing-road detection, and near-crash events identification were also included in this report. The roadside-LiDAR data-processing procedure includes new algorithms of LiDAR-data background filtering, LiDAR-point clustering, cluster classification (vehicles and pedestrians), object tracking and trajectory calculation. The methods for processing roadside LiDAR and pilot applications of using LiDAR trajectory data will serve as a foundation for new connected/autonomous traffic infrastructure advanced by 360-degree edge LiDAR sensors. Road-side LiDAR is new technology to fill the data gap of unconnected multimodal traffic in connected and autonomous traffic systems and will innovate traffic engineering/research areas with all-traffic trajectory data that was not available in traditional traffic sensing systems.
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