Unmanned Aerial Vehicle Path Planning for Traffic Estimation and Detection of Non-Recurrent Congestion

Unmanned aerial vehicles (drones) can be used in traffic and road monitoring applications. The authors investigate the benefit of using drones for simultaneous traffic state estimation and incident detection. Specifically, the authors propose a coupled planning and estimation framework where the authors adaptively navigate a drone to minimize the uncertainty on parameter and traffic state estimates. The authors show that the use of a drone provides significant improvement in incident detection under congested conditions. Without a drone, the estimation procedure in congested conditions is not able to distinguish between observations due to congestion under normal operating conditions and similar observations due to a reduction in capacity.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AFB80 Standing Committee on Geospatial Data Acquisition Technologies.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Yahia, Cesar N
  • Scott, Shannon E
  • Boyles, Stephen D
  • Claudel, Christian G
• Conference:
  • Transportation Research Board 98th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2019-1-13 to 2019-1-17
• Date: 2019

Language

• English

Media Info

• Media Type: Digital/other
• Features: References;
• Pagination: 4p

Subject/Index Terms

• TRT Terms: Drones; Incident detection; Traffic congestion; Traffic flow; Traffic surveillance; Trajectory control
• Subject Areas: Aviation; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01697982
• Record Type: Publication
• Report/Paper Numbers: 19-01455
• Files: TRIS, TRB, ATRI
• Created Date: Mar 1 2019 3:51PM