Design andAnalysis ofaTwoStage Traffic Light System Using Fuzzy Logic


Figure 5: Queue membership. Figure 6



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design and analysis of a two stage traffic light system using fuzzy

Figure 5:
Queue membership.
Figure 6: 
Time
r
membership.
Figure 7:
Urgency membership.
Figure 8:
Queue-Lane-1 membership.


Volume 5 • Issue 3 • 1000162
J Inform Tech Softw Eng
ISSN: 2165-7866 JITSE, an open access journal
Citation:
Alam J, Pandey MK (2015) 
Design and Analysis of a Two Stage Traffic Light System Using Fuzzy Logic. 
J Inform Tech Softw Eng 5: 162. 
doi:
10.4172/2165-7866.1000162
Page 7 of 9
fuzzy rules are used for designingTUDM and ETDM shown in the 
Figure 11 and 12 respectively. 
In the fuzzy logic controller once the appropriate rules are fired, 
the degree of membership of the output fuzzy variable i.e.,, Urgency is 
determined by encoding the antecedent fuzzy subsets in this case Queue, 
Time
r
and the output fuzzy variable i.e., Extension-time is determined 
by encoding the antecedent fuzzy subsets, in this case Queue-Lane-1, 
Queue-Lane-2. In two stage traffic light system using fuzzy logic the 
max-min implication technique is used. Using this technique the final 
output membership function for each rule is the fuzzy set assigned to 
that output by clipping the degree of truth values of the membership 
functions of the associated antecedents. Once the membership degree 
of each output fuzzy variable is determined all of the rules that are 
being fired are then combined and the actual crisp output is obtained 
through defuzzification. The procedure of converting each aggregated 
fuzzy output set into a single crisp value is called defuzzification. In 
traffic urgency decision module and extension time decision modules 
we use centroid defuzzification method.

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