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Remote Sens. 2014, 6(11), 11315-11341; doi:10.3390/rs61111315

An Operational System for Estimating Road Traffic Information from Aerial Images

German Aerospace Center (DLR), Remote Sensing Technology Institute, 82234 Wessling, Germany
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Received: 4 June 2014 / Revised: 3 November 2014 / Accepted: 4 November 2014 / Published: 13 November 2014
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Abstract

Given that ground stationary infrastructures for traffic monitoring are barely able to handle everyday traffic volumes, there is a risk that they could fail altogether in situations arising from mass events or disasters. In this work, we present an alternative approach for traffic monitoring during disaster and mass events, which is based on an airborne optical sensor system. With this system, optical image sequences are automatically examined on board an aircraft to estimate road traffic information, such as vehicle positions, velocities and driving directions. The traffic information, estimated in real time on board, is immediately downlinked to a ground station. The airborne sensor system consists of a three-head camera system, a real-time-capable GPS/INS unit, five industrial PCs and a downlink unit. The processing chain for automatic extraction of traffic information contains modules for the synchronization of image and navigation data streams, orthorectification and vehicle detection and tracking modules. The vehicle detector is based on a combination of AdaBoost and support vector machine classifiers. Vehicle tracking relies on shape-based matching operators. The processing chain is evaluated on a large number of image sequences recorded during several campaigns, and the data quality is compared to that obtained from induction loops. In summary, we can conclude that the achieved overall quality of the traffic data extracted by the airborne system is in the range of 68% and 81%. Thus, it is comparable to data obtained from stationary ground sensor networks. View Full-Text
Keywords: monitoring; pattern recognition; orthorectification; georeferencing; sequences; tracking; vehicle detection monitoring; pattern recognition; orthorectification; georeferencing; sequences; tracking; vehicle detection
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Leitloff, J.; Rosenbaum, D.; Kurz, F.; Meynberg, O.; Reinartz, P. An Operational System for Estimating Road Traffic Information from Aerial Images. Remote Sens. 2014, 6, 11315-11341.

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