|M.Sc Student||Eden Niv|
|Subject||Adaptive Signal Control under Congestion based on Fuzzy|
|Department||Department of Civil and Environmental Engineering||Supervisor||Professor David Mahalel|
The aim of the research is to develop a signal control method for partially or fully congested intersections. As a result, the congestion period is shortened, delays are reduced and the environmental impacts of traffic are reduced.
Maximizing the intersection throughput is achieved through a fuzzy logic control model.
In the first stage of the research, a mathematical model was chosen to serve as a basis for the fuzzy control model. The second stage defined the control process. The control model included definitions of input variables, output variables and a primary characterization of the rule bases' structure. At the next stage, the control model was adapted to a fully functional fuzzy control model, i.e. definitions of the term sets, of input and output variables. Component functions were fitted to the term sets and the rule base was completed. The performance of the fuzzy control model was compared to the performance of a conventional signal control model. A simulation program developed in this research achieved the evaluation of the control methods.
The research results show that during congestion, the maximum throughput is achieved with the fuzzy control and this type of control is superior to other control methods.