Enhanced adaptive traffic signal control system using camera sensor and embedded system

Traffic plays an important role in social stability and community development. Without an appropriate traffic signal control system, the possibility of traffic congestion will be very high and causes various negative impacts. The traffic signal control system with video camera sensor is implemented in embedded systems using BeagleBoard-xM. The system uses Viola-Jones method and Haar Training in detecting the vehicle object from a video frame. Then, Euclidean distance and kalman filter methods are used in tracking the vehicle. The ability of kalman filter in predicting the next position of the object is a very important feature for multi-object tracking. The number of counted vehicles in each lane at the intersection then will be processed using Fuzzy Logic to determine optimal cycle time and split time.