Paper Type |
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Research Paper |
Title |
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Traffic Signal Controller for Mixed Traffic Conditions |
Country |
: |
Indonesia |
Authors |
: |
Budi Yulianto, Setiono |
 |
: |
10.9790/1684-0411826  |
Abstract:Fuzzy logic has been widely used to develop an adaptive traffic signal controller because it allows
qualitative modelling of complex systems. However, existing research has developed Fuzzy Logic Traffic Signal
Controller (FLTSC) based on non-mixed traffic conditions. These FLTSC are not appropriate to the mixed
traffic conditions of developing countries where the traffic streams consist of different types of vehicles with a
wide variation in their static, dynamic and operating characteristics.
This paper describes the design and evaluation of an adaptive traffic signal controller based on fuzzy
logic for an isolated four-way intersection with specific reference to mixed traffic in developing countries. The
controller is designed to be responsive to real-time traffic demands. Video image processing has been proposed
to capture traffic data such as maximum queue length (in metres) and average occupancy rate (in %) from each
approach of the intersection. The proposed FLTSC uses maximum queue lengths and average occupancy rates
collected during the previous cycle in order to estimate the number of seconds of green time required by each
set of signal groups (stage) during the next cycle.
Keywords:-fuzzy logic, mixed traffic, signal control
[1] Strobel, H, Computer Controlled Urban Transport, Ed. John Wiley, 1982.
[2] Kell, J.H. and Fullerton, I.J., Manual of traffic signal design – Chapter 7: Detectors. Institute of Transportation Engineers, Prentice
Hall, Englewood Cliffs, New Jersey, 1991.
[3] Lee, J.H., Lee, K.M. and Leekwang, H., Fuzzy controller for intersection group. International IEEE/IAS Conference on Industrial
Automation and Control, Taipei, Taiwan, 1994, pp. 376-382.
[4] Trabia, M.B. and Kaseko, M.S., A fuzzy logic controller for a traffic signal. IASTED International Conference on Applications of
Control and Robotics, Orlando, Florida, January 1996, pp. 117-122
[5] Kim, J., A fuzzy logic control simulator for adaptive traffic management, IEEE International Conference on Fuzzy Systems, vol. 3,
1997, pp. 1519-1524.
[6] Bell, M.G.H., Future directions in traffic signal control. Transportation Research Part A, Vol. 26A, No. 4, 1992, pp. 303-313.
[7] Trabia, M.B., Kaseko, M.S. and Ande, M., A two-stage fuzzy logic for traffic signals. Transportation Research Part C, Vol. 7, No.
7, 1999, pp. 353-367.
[8] Bång, K.L., Optimal control of isolated traffic signals. Traffic Engineering and Control, Vol. 17, No. 7, July, 1976, pp. 288-292.
[9] Vincent, R.A. and Young, C.P., Self-optimising traffic signal control using microprocessors – the TRRL MOVA strategy for
isolated intersections. Traffic Engineering and Control, Vol. 27, No. 7, 1986, pp. 385-387.
[10] Zadeh, L.A., Fuzzy sets. Information and Control, Vol. 8, 1965, pp. 338-353.