With the development of GPS-based navigation, computer and communication, intelligent vehicle
navigation system will play a more important role in future transportation systems. Vehicle-borne GPS
can provide positioning and navigation information quickly and accurately at relatively low cost. GPS
has made a significant impact on almost all positioning and navigation applications including vehicle-borne
GPS intelligence navigation system (VINS) (Allison, et al., 1999; Haddad, et al., 1999; He et al.,
1998; Hu et al., 2000). However, GPS alone is insufficient to maintain continuous positioning because
of inevitable obstructions caused by buildings and other natural features. When GPS signals are
blocked or lost, the precision of positioning will be reduced to unacceptable level. Therefore, it is
necessary to improve the accuracy and reliability of VINS.
This paper presents three methods to improve the accuracy and reliability of VINS, viz., dead
reckoning (DR), differential GPS (DGPS) and map matching. The advantages and disadvantages of these augmentation methods are analyzed. The results of a real application and simulation experiments
are also provided. Further suggestions to assure the accuracy and reliability of VINS are also proposed.
Dead Reckoning (DR) Method
Dead reckoning method determine a vehicle’s position relative to an initial location by integrating
measured distance increments and directions of travel (Hong, 1997). The distance increments are
measured using a distance sensor. The directions can be derived through a course sensor. When there
GPS signals are degraded, the position of a vehicle at ti epoch can be determined from the direction
angle (α ) and distance (D) components:
) the initial position at t0
) the position at ti
distance and direction from (X0
) at tk
The course sensor could be derived from geomagnetism, gyroscope or using information from the
difference between the velocity of the left tyre and right tyre. The distance sensor may be tapped from
the vehicle’s odometer or from a velocity sensor. The navigation accuracy of DR is a function of the
distance traveled. Longer distances tend to incur greater accumulated errors. Errors of DR are mainly
caused by characteristics of the sensors and from environmental factors such as terrain and uneven tyre
pressures. Hence, DR per sec cannot be used over a long period. Navigation system which combines
measurements from both DR and GPS system can mitigate the errors by continuously calibrating DR
sensors by acquired GPS positions
Another mode of DR system is INS (Inertial Navigation System) which can continuously provide
direction and acceleration (Yuan, et al., 1993). Starting from a known position, INS uses the variations
in positions to determine the trail of a vehicle. Errors of INS increase with the square of time. Hence,
INS alone has its limitations. However, a combined GPS and INS solution could overcome
shortcomings of each other and is an effective method for providing continuous and precise navigation
for vehicles. Examples can be seen from literature of Allison, et al., (1999).
Differential GPS (DGPS) Method
VINS belongs to a class of real time kinematic positioning whose precision is relatively low. In order
to increase its precision, one method is to introduce differential GPS (DGPS) technique. DGPS can
reduce or cancel error sources such as satellite clock bias, atmosphere delays, orbit bias. According to
the different modes of operation, DGPS can be divided into three classes: position-based DGPS,
pseudorange DGPS and carrier phase DGPS (Wang, et al., 1996; Hofmann-Wellenhof, et al., 1997).
The principles are basically the same but corrected sophistication and precision levels of each
technique are quite different. In VINS, position-based DGPS and pseudorange DGPS are usually used.
Fig. 1 shows that the precision of VINS can be improved to a meter level by using position or
pseudorange DGPS (Wang, et al, 1996). Therefore, DGPS is a relevant method to increase the
precision of VINS. With improved positions, the calibration of the sensors of DR system will have
consequential improvements as well. The effect of using DGPS method to improve the performance of
GPS within the urban environment is documented in Allison, et al., (1999).