High-Resolution Micro Traffic Data From Roadside LiDAR Sensors for Connected-Vehicles and New Traffic Applications

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.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Figures; Maps; Photos; References; Tables;
  • Pagination: 69p

Subject/Index Terms

Filing Info

  • Accession Number: 01695814
  • Record Type: Publication
  • Report/Paper Numbers: P224-14-803 TO15
  • Contract Numbers: DTRT13-G-UTC55; P224-14-803/TO #15
  • Files: UTC, NTL, TRIS, ATRI, USDOT, STATEDOT
  • Created Date: Jan 7 2019 10:57AM