Estimated Vehicle Density Based on Video Processing Using the Gaussian Mixture Model Method

Abstract

Congestion is a problem that cannot be decomposed properly, especially at big cities in Indonesia, one of them is in Surabaya. To solve this problem is needed to observe characteristics of the road such as the number of vehicles, vehicle speed and vehicle density. This research took the data in several areas in Surabaya by put the camera in the middle of a crossing bridge. This research aims to determine the density value by comparing traffic volume with vehicle speed. The value of speed and number of vehicles can be known using Gaussian Mixture Model method, where object detection is detected by background substraction process, which is video divided into several frames and in each frame images is divided into two part there are foreground and background. The object will be count 1 when blob analysis detect the foreground. In the theory to know the density value of a traffic flow, with compare the number of vehicles and the speed of vehicle. From the data has been taken, it is known that the number of vehicles is opposite with average speed the vehicle that passes. If average velocity of vehicle greater than the number of vehicle so the value density vehicle getting smaller . so that information can be found that the road is experiencing congestion conditions.