AC-UAV System for Complete Vehicle Coverage Trajectory Reconstruction: Methodology Framework and Field Experiment

Complete vehicle coverage trajectory data is of fundamental importance to traffic signal control strategy and intelligent transport system (ITS). There are mainly two categories in traffic data collection: stationary and mobile sensing. However, neither can offer near-complete spatial and temporal coverage, especially at traffic signals. This study first proposes a full-scale automated and connected UAV (AC-UAV) system, which consists of transformable UAVs with automated landing and take-off capabilities, cooperative charging piles, and a fleet management center. Secondly, based on the developed AC-UAV system, the authors introduce a 3-step methodological framework: multiple vehicle detection algorithm (MVD) based on deep learning and multiple vehicle tracking (MVT) algorithm based on data feature association and trajectories reconstruction. The field experiments were conducted in Xi’an, China. The results show that the proposed framework based on the AC-UAV system is capable of conducting mobile complete traffic data analysis tasks and also feasible for large-scale automated city applications.

• Record URL:
  • https://doi.org/10.1061/9780784483053.106
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784483053
• Supplemental Notes:
  • © 2020 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Wang, Kaiping
  • Yang, Rong
  • Shi, Dahu
  • Li, Meng
• Conference:
  • 20th COTA International Conference of Transportation Professionals
  • Location: Xi’an , China
  • Date: 2020-8-14 to 2020-8-16
• Publication Date: 2020

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 1255- 266
• Monograph Title: CICTP 2020: Transportation Evolution Impacting Future Mobility

Subject/Index Terms

• TRT Terms: Algorithms; Data collection; Field tests; Machine learning; Traffic data; Unmanned aircraft systems; Vehicle detectors; Vehicle trajectories
• Geographic Terms: Xi'an (China)
• Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01767405
• Record Type: Publication
• ISBN: 9780784483053
• Files: TRIS, ASCE
• Created Date: Mar 22 2021 10:34AM