05-07-2012, 12:00 PM
Fuzzy Logic Based Traffic Light Controller
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INTRODUCTION
signals are common features of urban areas
throughout the world, controlling number of vehicles.
Their main goals are improving the traffic safety at the
intersection, maximizing the capacity at the intersection
and minimizing the delays.
Thus careful design of traffic signal control would result in
increasing the efficiency of the road network to yield
economical and environmental benefits. In a conventional
traffic light controller, the traffic lights change at constant
cycle time. The other type of traffic light controllers used
in current practice, are based on the ‘time-of-the day’
scheme.
FUZZY TRAFFIC SIGNAL CONTROL
In this paper, the implementation of fuzzy logic controller
for the traffic flow control is discussed. Fuzzy logic
technology has the capability of mimicking the human
intelligence for controlling the traffic flow. It allows the
implementation of real-life rules similar to the way in
which humans would think. The theory of fuzzy logic is
based on concepts graded to handle uncertainties and
imprecision in a particular domain of knowledge. The
graded concepts are useful since real situations in traffic
control are very often not deterministic and cannot be
described precisely.
SIMULATION OF THE TRAFFIC AT AN ISOLATED INTERSECTION
A signalised intersection with 4 approaches and typical
vehicle detectors is considered as shown in fig 1. Vehicle
detectors are installed on ‘upstream-line’ and ‘stop-line’.
The number of approaching vehicles for each approach
during given time interval can be estimated using the
detectors. Fuzzy variables considered are arriving vehicles
(A), queuing vehicles (Q) and extension (EXT).
The membership functions for the arriving vehicles (A) at
the approach having green phase are few = -4 to 4,
small = 0 to 8, medium = 4 to 12 and many = 8 to 16.
The membership functions for the queuing vehicles (Q) at
the next approach having red phase are few = -4 to 4,
small = 0 to 8, medium = 4 to 12 and many = 8 to 16.
RESULTS
The above two algorithms of fuzzy rule base are
implemented using MATLAB tool. An isolated Traffic
Intersection is simulated in Visual Basic 6 environment.
Sample screen shot for the same is as attached herewith.