Abstract: Traffic congestion has become a major problem in
many countries. One of the main causes of traffic congestion is due
to road merges. Vehicles tend to move slower when they reach the
merging point. In this paper, an enhanced algorithm for traffic
simulation based on the fluid-dynamic algorithm and kinematic wave
theory is proposed. The enhanced algorithm is used to study traffic
congestion at a road merge. This paper also describes the
development of a dynamic traffic simulation tool which is used as a
scenario planning and to forecast traffic congestion level in a certain
time based on defined parameter values. The tool incorporates the
enhanced algorithm as well as the two original algorithms. Output
from the three above mentioned algorithms are measured in terms of
traffic queue length, travel time and the total number of vehicles
passing through the merging point. This paper also suggests an
efficient way of reducing traffic congestion at a road merge by
analyzing the traffic queue length and travel time.
Abstract: In this paper, an extended study is performed on the
effect of different factors on the quality of vector data based on a
previous study. In the noise factor, one kind of noise that appears in
document images namely Gaussian noise is studied while the previous
study involved only salt-and-pepper noise. High and low levels of
noise are studied. For the noise cleaning methods, algorithms that were
not covered in the previous study are used namely Median filters and
its variants. For the vectorization factor, one of the best available
commercial raster to vector software namely VPstudio is used to
convert raster images into vector format. The performance of line
detection will be judged based on objective performance evaluation
method. The output of the performance evaluation is then analyzed
statistically to highlight the factors that affect vector quality.