Implementation vehicle classification on distributed traffic light control system neural network based

Distributed Traffic System Control System is a real-time adaptive traffic light system with traffic condition for minimize the probabilty of traffic congestion. So far, the research of Distributed Traffic Light Control System has been developed with Principle Component Analysis (PCA) as the recognition method to identify vehicle object. The recognizition can be optimized using classification system that can identify an object to more spesific class as large cars like bus and truck, or minicars like van, jeep, and sedan. Classification systems has be implemented with neural network algorithm specifically Backpropagation, Fuzzy Learning Vector Quantization (FLVQ), and Fuzzy Learning Quantization Particle Swarm Optimization (FLVQ-PSO).