Affiliations: [a] School of Automation, Nanjing Institute of Technology, Nanjing, China
| [b] Key Laboratory of Measurement and Control of CSE, Ministry of Education, Southeast University, Nanjing, China
| [c] School of Modern Posts & Institute of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing, China
| [d] School of Automation, Southeast University, Nanjing, China
Abstract: Traffic congestion has become a serious phenomenon in the cities. In order to achieve the effective control of intersections, multi-lane four-phase intersection is studied. The corresponding queue length model and vehicular delay model are established. Aiming at the dynamic uncertainty problem in the intersection, a type-2 fuzzy logic controller is designed. The green time of each phase is dynamically decided according to the real-time traffic information for purpose of achieving the smallest vehicular average delay, so as to enhance the traffic efficiency in the intersection. The excellent performance of the designed controller is confirmed through simulation experiments under different conditions. Finally, in view of the difficulty of parameter settings in type-2 fuzzy controller, DNA evolutionary algorithm is applied to online optimize and adjust the parameters of membership function. One group of parameters is difficult to fit all traffic situations, so on-line optimization and adjustment is necessary for reflecting the real-time change of traffic flow in time, which is of great significance for the practical application. The experimental results indicate that the online optimized type-2 fuzzy traffic control method has better effect.
Keywords: Type-2 fuzzy logic control, traffic signal control, optimization, DNA evolutionary algorithm
