Abstract:
As Traffic congestion is becoming an everyday
facing problem in urban region, monitoring road and
Traffic prediction system are playing an important role
in the city life. The previous Traffic Prediction Systems
were implemented depending on the road network
sensor. These technologies had been prompted by the
need of addressing to solve the problem installation
and maintenance cost. Fortunately the dramatic
technology innovation is carrying many crucia solution
for Transportation agency to provide the relative
services efficiently. This paper mainly emphasizes
detecting Traffic condition by analyzing the behavior of
vehicle primarily based on applying GPS enable
Mobile phone and integrating the underlying
Transportation network information and history data.
The system is built into two parts: Client (Mobile
device) and Cloud Backend Server. On the Client side,
the system distinguishes whether the Mobile device
carrier is taking a vehicle or walking. The Average
Moving Filtering method and the measurement of total
distance are utilized in analyzing mode of
Transportation. The distance of two points (latitude
and longitude) is computed by using Haversine
Formula. On the Server side, it detects the Traffic
status based on checking the behavior of vehicle based
on the Client result by applying Bayes Classifier.
