Unmanned aerial vehicle path planning for traffic estimation and detection of non-recurrent congestion

Unmanned aerial vehicles (UAVs) provide a novel means of extracting road and traffic information from video data. In particular, by analyzing objects in a video frame, UAVs can detect traffic characteristics and road incidents. Leveraging the mobility and detection capabilities of UAVs, the authors investigate a navigation algorithm that seeks to maximize information on the road/traffic state under non-recurrent congestion. The authors propose an active exploration framework that (1) assimilates UAV observations with speed-density sensor data, (2) quantifies uncertainty on the road/traffic state, and (3) adaptively navigates the UAV to minimize this uncertainty. The navigation algorithm uses the A-optimal information measure (mean uncertainty), and it depends on covariance matrices generated by a dual state ensemble Kalman filter (EnKF). The authors' results indicate that targeted UAV observations aid in the detection of incidents under congested conditions where speed-density data are not informative.

• Record URL:
  https://doi.org/10.1080/19427867.2021.1951524
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19427867
• Supplemental Notes:
  • © 2021 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Yahia, Cesar N
  • Scott, Shannon E
  • Boyles, Stephen D
  • Claudel, Christian G
• Publication Date: 2022-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 849-862
• Serial:
  • Transportation Letters: The International Journal of Transportation Research
  • Volume: 14
  • Issue Number: 8
  • Publisher: Taylor & Francis
  • ISSN: 1942-7867
  • EISSN: 1942-7875
  • Serial URL: http://www.tandfonline.com/toc/ytrl20/current

Subject/Index Terms

• TRT Terms: Data collection; Detection and identification; Drones; Nonrecurrent congestion; Traffic data; Traffic surveillance; Trajectory control; Video
• Subject Areas: Aviation; Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01861029
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 13 2022 9:25AM