Tracing Traffic Dynamics With Remote Sensing
Author(s)
S. P. Hoogendoorn & H. J. van Zuylen
Abstract
Science has not yet been completely successful in explaining the various
puzzling but interesting phenomena of congested traffic flows. The reasons that
these phenomena are poorly understood are mainly due to the lack of adequate
data needed to develop this theory. Common measurement methods collect only
‘snapshots’ of the situation (i.e. at a limited number of cross-sections, or a single,
instrumented vehicle). Such data do not provide sufficient information to study
the dynamics of individual drivers in their continuously changing traffic and
roadway environment.
This paper presents a new innovative traffic data collection system to detect
and track vehicles from aerial image sequences. Besides the longitudinal and
lateral positions as a function of time, the system can also determine the vehicle
lengths and widths. Before vehicle detection and tracking can be achieved, the
software handles correction for lens distortion, radiometric correction, and
orthorectification of the image. Vehicle detection occurs approximately each
tenth of a second, after which vehicles are tracked both forward and backward in
time (10 frames in each direction). The resulting data redundancy is then used to
improve accuracy and reliability of the traffic data. Post-processing furthermore
entails using Iterative Extended Kalman filtering to improve data quality.
The software was tested on data collected from a helicopter, using a digital
camera gathering high-resolution monochrome images of a Dutch motorway
near the city of Utrecht. From the test, it is concluded that the techniques for
analyzing the digital images can be applied automatically without many
problems, while nearly 100% of all vehicles could be detected and tracked.
1 Introduction
The objective of the present study is to develop a data collection method to
collect vehicle trajectories (longitudinal and lateral position of the centre of the
Keywords
Related Book
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