Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26059
Title: Unmanned Aerial Vehicle-Based Traffic Analysis: A Case Study for Shockwave Identification and Flow Parameters Estimation at Signalized Intersections
Authors: KHAN, Muhammad Arsalan 
ECTORS, Wim 
BELLEMANS, Tom 
JANSSENS, Davy 
WETS, Geert 
Issue Date: 2018
Source: Remote Sensing, 10(3) (Art N° 458)
Abstract: Owing to their dynamic and multidisciplinary characteristics, Unmanned Aerial Vehicles (UAVs), or drones, have become increasingly popular. However, the civil applications of this technology, particularly for traffic data collection and analysis, still need to be thoroughly explored. For this purpose, the authors previously proposed a detailed methodological framework for the automated UAV video processing in order to extract multi-vehicle trajectories at a particular road segment. In this paper, however, the main emphasis is on the comprehensive analysis of vehicle trajectories extracted via a UAV-based video processing framework. An analytical methodology is presented for: (i) the automatic identification of flow states and shockwaves based on processed UAV trajectories, and (ii) the subsequent extraction of various traffic parameters and performance indicators in order to study flow conditions at a signalized intersection. The experimental data to analyze traffic flow conditions was obtained in the city of Sint-Truiden, Belgium. The generation of simplified trajectories, shockwaves, and fundamental diagrams help in analyzing the interruptedflow conditions at a signalized four-legged intersection using UAV-acquired data. The analysis conducted on such data may serve as a benchmark for the actual traffic-specific applications of the UAV-acquired data. The results reflect the value of flexibility and bird-eye view provided by UAV videos; thereby depicting the overall applicability of the UAV-based traffic analysis system. The future research will mainly focus on further extensions of UAV-based traffic applications.
Notes: Khan, MA (reprint author), Show less UHasselt Hasselt Univ, Transportat Res Inst IMOB, Agoralaan, B-3590 Diepenbeek, Belgium. muhammadarsalan.khan@uhasselt.be; wim.ectors@uhasselt.be; tom.bellemans@uhasselt.be; davy.janssens@uhasselt.be; geert.wets@uhasselt.be
Keywords: drones; UAVs; traffic data; traffic data collection; traffic flow analysis; vehicle trajectories; shockwave analysis
Document URI: http://hdl.handle.net/1942/26059
Link to publication/dataset: http://www.mdpi.com/2072-4292/10/3/458
e-ISSN: 2072-4292
DOI: 10.3390/rs10030458
ISI #: 000428280100104
Rights: © 2018 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Category: A1
Type: Journal Contribution
Validations: ecoom 2019
Appears in Collections:Research publications

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