Citation

Barmpounakis EN, Vlahogianni EI, Golias JC, Babinec A. Transp. Lett. 2019; 11(6): 332-340.

Copyright

(Copyright © 2019, Maney Publishing, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/19427867.2017.1354433

PMID

unavailable

Abstract

Small Unmanned Aerial Vehicles (sUAV or drones) have been one of the latest tools for monitoring transportation infrastructure and operations. Their lower cost compared to current fixed location camera systems or Manned Aerial Vehicles (MAV) and their ability to read just their view area depending on the situation they face, make them a promising tool of collecting both macroscopic and microscopic data. However, although drone technology and computer vision techniques are advancing fast, there is little information on how accurate and reliable they are for collecting microscopic traffic data. In this paper, we examine the potential of using sUAV as part of the ITS infrastructure as a way of extracting naturalistic trajectory data from aerial video footage from a low volume four-way intersection and a pedestrian passage. Moreover, the accuracy of speed data collected from a drone compared to data collected from an On-Board Diagnostics II (OBD-II) device is examined. For this, a controlled experiment where the vehicle was driven in various speeds and the drone flew in ranging altitudes was conducted.

RESULTS show that accuracy is highly dependent on the stabilization of the video and the geo-reference procedure. Moreover, the capabilities of such systems are examined in traffic applications and the way they can be part of future transportation infrastructure is discussed.

Language: en

Keywords

computer vision; drones; intelligent transportation systems; microscopic traffic data; Unmanned aerial vehicles