Open AccessDYNAMIC BEHAVIOUR OF A MODELED TRANSPORTATION NETWORKED CONTROL SYSTEM FOR T-JUNCTION
Author(s) -
Olubusola Olufunke Nuga,
Kamoli Amusa,
Ayorinde Joseph Olanipekun,
A. Adewusi
Publication year - 2017
Publication title -
journal of natural sciences, engineering and technology/journal of natural science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2315-7461
pISSN - 2277-0593
DOI - 10.51406/jnset.v16i1.1804
Subject(s) - intersection (aeronautics) , fuzzy logic , controller (irrigation) , control theory (sociology) , traffic flow (computer networking) , computer science , matlab , fuzzy control system , real time computing , signal timing , control engineering , simulation , engineering , traffic signal , control (management) , transport engineering , computer network , artificial intelligence , agronomy , biology , operating system
Traffic congestion has been the major problem on most Nigeria roads. This is particularly due to the rapid increase in urban migration. Majority of the traffic control schemes adopted in the country to alleviate this problem are the fixed time controllers employed at all signalized intersections. This has resulted in increased traffic jam especially during the peak periods at most intersections on our highways. In this study, a fuzzy logic system to control traffic on signalized intersection has been proposed. The Fuzzy Logic Controller regulates the traffic signal timing, the green light extension and phase sequence to ensure smooth flow of traffic, thereby reducing traffic delays and thus increasing the intersection capacity. A fuzzy logic traffic control simulation model was developed and tested using MATLAB/ SIMULINK software. Comparative analysis was carried out between the fuzzy logic controller and a conventional fixed-time controller in order to determine the efficiency of the developed system. Evaluation results of the fuzzy logic traffic controller shows that vehicles spent less time at the intersection compared to the fixed time controller, that is, improved vehicular movement. Moreover, simulation results show that the fuzzy logic controller has better efficiency and that a huge improvement could be realized by adapting it in controlling traffic flow at intersections.