39,665 research outputs found
Trajectory Clustering and an Application to Airspace Monitoring
This paper presents a framework aimed at monitoring the behavior of aircraft
in a given airspace. Nominal trajectories are determined and learned using data
driven methods. Standard procedures are used by air traffic controllers (ATC)
to guide aircraft, ensure the safety of the airspace, and to maximize the
runway occupancy. Even though standard procedures are used by ATC, the control
of the aircraft remains with the pilots, leading to a large variability in the
flight patterns observed. Two methods to identify typical operations and their
variability from recorded radar tracks are presented. This knowledge base is
then used to monitor the conformance of current operations against operations
previously identified as standard. A tool called AirTrajectoryMiner is
presented, aiming at monitoring the instantaneous health of the airspace, in
real time. The airspace is "healthy" when all aircraft are flying according to
the nominal procedures. A measure of complexity is introduced, measuring the
conformance of current flight to nominal flight patterns. When an aircraft does
not conform, the complexity increases as more attention from ATC is required to
ensure a safe separation between aircraft.Comment: 15 pages, 20 figure
A Force-Directed Approach for Offline GPS Trajectory Map Matching
We present a novel algorithm to match GPS trajectories onto maps offline (in
batch mode) using techniques borrowed from the field of force-directed graph
drawing. We consider a simulated physical system where each GPS trajectory is
attracted or repelled by the underlying road network via electrical-like
forces. We let the system evolve under the action of these physical forces such
that individual trajectories are attracted towards candidate roads to obtain a
map matching path. Our approach has several advantages compared to traditional,
routing-based, algorithms for map matching, including the ability to account
for noise and to avoid large detours due to outliers in the data whilst taking
into account the underlying topological restrictions (such as one-way roads).
Our empirical evaluation using real GPS traces shows that our method produces
better map matching results compared to alternative offline map matching
algorithms on average, especially for routes in dense, urban areas.Comment: 10 pages, 12 figures, accepted version of article submitted to ACM
SIGSPATIAL 2018, Seattle, US
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