TRAFFIC MANAGEMENT WITH STATE-OF-THE-ART AIRBORNE IMAGING SENSORS
C. K. Toth*, D. Grejner-Brzezinska b
^OSU, Center for Mapping, 1216 Kinnear Road, Columbus, OH 43212-1154, USA — toth(@cfim.ohio-state.edu
*OSU, Department of Civil and Environmental Engineering and Geodetic Science, Columbus, USA
Commission II, WG II/3
KEY WORDS: LiDAR, digital camera, traffic flow
ABSTRACT:
In recent years remote sensing has made remarkable technological progress and has significantly expanded into several application
fields. The rapid technological advances have come with the potential to widen the range of applications and to go beyond
conventional mapping. Technical aspects of using high-resolution airborne imagery and LiDAR to support traffic flow monitoring
and management are discussed in this paper. The primary objective of this ongoing research effort is to assess the feasibility and
reliability of extracting moving objects over transportation corridors, and the accuracy of their velocity estimation. This
investigation includes airborne LiDAR, video and high-performance digital camera imagery. A review on the potential of using
CCD and airborne laser scanning technology for transportation applications, especially for identifying and tracking moving objects
on the roads is provided.
1. INTRODUCTION
Unprecedented technological developments characterize the
last five years in spatial data acquisition and processing,
resulting in a paradigm shift in spatial information sciences
and totally revolutionizing airborne surveying practice:
e New active imaging sensors were introduced, such as
LiDAR, which almost immediately became the most
important source of terrain data.
e GPS/IMU-based direct georeferencing, essential to
several new sensors, including LiDAR and IfSAR,
became the primary technique for sensor orientation.
e |-meter commercial satellite imagery was introduced.
e Aerial photography experienced a major milestone, as
digital cameras reached and in fact surpassed the
performance of analog large format aerial cameras.
These advances in sensor technology lead to increased
volumes of data along with more complex data types, which,
in turn, demands higher automation of the data processing. In
fact, the boundaries of spatial information sciences are
becoming less defined as we enter the new age of
telegeoinformatics (Grejner-Brzezinska et. al., 2004a).
The rapidly increasing use of the new sensor data with rich
information content presents a potential for new applications
that could go beyond conventional mapping. Mapping of
man-made objects with terrain features, such as urban
mapping or corridor mapping of transmission and
transportation lines, is probably the most common mapping
task, which is primarily concerned with the static part of the
object space. However, these are probably the most dynamic
areas in terms of human activities. Most importantly the
traffic, including a variety of vehicles and various dynamics
presents a formidable challenge for the mapping processes,
as moving objects should be identified and removed. Instead
of throwing away the removed objects, it is very
advantageous to use these data to derive valuable information
for traffic monitoring and management. This paper is focused
on detecting moving objects on the roads by using airborne
remote sensing to support traffic flow information gathering.
The research described is supported by the National
Consortium for Remote Sensing in Transportation-Flows
848
(NCRST-F), sponsored by the U.S. DOT and NASA.
NCRST-F was established in 2000 as a Consortium of three
universities: The Ohio State University, George Mason
University and the University of Arizona
(http://www.nerst.org/research/nerst-f/ncrst-£ home.html).
The primary goal of the Consortium is to improve the
efficiency of the transportation system at the national, state
and local levels, by integrating remotely sensed traffic flow
data obtained from airborne and/or satellite platforms with
traditional data collected from the ground. It should be
emphasized that the important features that are unique to
remote sensing in traffic monitoring are: (1) sensors are not
attached to just one location (for example, track dangerous
cargo or incidents), (2) sensors can be deployed during
special events (natural disasters, evacuation), (3) remote
sensing can provide superior spatial resolution, and (4) can
provide up-to-date traveler information, if applied in real-
time.
This paper provides a review of research using state-of-the-
art remote sensing sensors to support traffic flow extraction
using LiDAR and digital camera sensors installed on
airborne platforms. The results from LiDAR corridor
mapping and helicopter-based road intersection monitoring
are discussed. It is important to note that rapid developments
of UAV technologies are expected to provide an additional
platform that is not only extremely cost-effective, but very
flexible to accommodate in terms of offering a wide variety
of platform altitude and velocity.
2. LIDAR TECHNOLOGY
LiDAR (or airborne laser scanning) systems have become a
dominant player in high-precision spatial data acquisition in
the late 90's. Installed in aircraft and helicopters, these
active sensor systems can deliver surface data at decimeter-
level vertical accuracy in an almost totally automated way.
In fact, this new technology has quickly established itself as
the main source of surface information in commercial
mapping. Despite the initial high price, these systems have
made remarkable market penetration. Recent technical and
algorithmic advances have further improved the capabilities
of this remote sensing technology. In particular, intensity
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