1 research outputs found
Context-aware GPS Integrity Monitoring for Intelligent Transport Systems (ITS)
The integrity of positioning systems has become an increasingly important requirement
for location-based Intelligent Transports Systems (ITS). The navigation systems, such
as Global Positioning System (GPS), used in ITS cannot provide the high quality
positioning information required by most services, due to the various type of errors
from GPS sensor, such as signal outage, and atmospheric effects, all of which are
difficult to measure, or from the map matching process. Consequently, an error in the
positioning information or map matching process may lead to inaccurate determination
of a vehicle’s location. Thus, the integrity is require when measuring both vehicle’s
positioning and other related information such as speed, to locate the vehicle in the
correct road segment, and avoid errors. The integrity algorithm for the navigation
system should include a guarantee that the systems do not produce misleading or faulty
information; as this may lead to a significant error arising in the ITS services. Hence, to
achieve the integrity requirement a navigation system should have a robust mechanism,
to notify the user of any potential errors in the navigation information.
The main aim of this research is to develop a robust and reliable mechanism to support
the positioning requirement of ITS services. This can be achieved by developing a high
integrity GPS monitoring algorithm with the consideration of speed, based on the
concept of context-awareness which can be applied with real time ITS services to adapt
changes in the integrity status of the navigation system. Context-aware architecture is
designed to collect contextual information about the vehicle, including location, speed
and heading, reasoning about its integrity and reactions based on the information
acquired.
In this research, three phases of integrity checks are developed. These are, (i)
positioning integrity, (ii) speed integrity, and (iii) map matching integrity. Each phase
uses different techniques to examine the consistency of the GPS information. A receiver
autonomous integrity monitoring (RAIM) algorithm is used to measure the quality of
the GPS positioning data. GPS Doppler information is used to check the integrity of
vehicle’s speed, adding a new layer of integrity and improving the performance of the
map matching process. The final phase in the integrity algorithm is intended to verify
the integrity of the map matching process. In this phase, fuzzy logic is also used to
measure the integrity level, which guarantees the validity and integrity of the map
matching results.
This algorithm is implemented successfully, examined using real field data. In addition,
a true reference vehicle is used to determine the reliability and validity of the output.
The results show that the new integrity algorithm has the capability to support a various
types of location-based ITS services.Saudi Arabia Cultural Burea