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Title:

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

Accession Number:

01697982

Record Type:

Component

Abstract:

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.

Report/Paper Numbers:

19-01455

Language:

English

Corporate Authors:

Transportation Research Board

Authors:

Yahia, Cesar N
Scott, Shannon E
Boyles, Stephen D
Claudel, Christian G

Pagination:

4p

Publication Date:

2019

Conference:

Transportation Research Board 98th Annual Meeting

Location: Washington DC, United States
Date: 2019-1-13 to 2019-1-17
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

References (13)

Subject Areas:

Aviation; Highways; Operations and Traffic Management

Source Data:

Transportation Research Board Annual Meeting 2019 Paper #19-01455

Files:

TRIS, TRB, ATRI

Created Date:

Dec 7 2018 9:43AM