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Simulation of Urban Traffic System using Sumo and Optimization of Real Traffic Signal Model using OpenCV Image Sensing Module


Vinay K. S , Dayananda Sagar College of Engineering; Bharath Inani, Dayananda Sagar College of Engineering, Bangalore - 78; Sachin Shejole, Dayananda Sagar College of Engineering, Bangalore - 78; Shreyas K, Dayananda Sagar College of Engineering, Bangalore - 78; Sushanth Vasista, Dayananda Sagar College of Engineering, Bangalore - 78


Signal Control, Traffic Simulation, Vehicle Density, Congestion, Optimization


Traffic flow analysis and modeling are an essential part of various traffic management applications (e.g signal control) and can provide a better insight into the state of traffic. The purpose of this work is to create a traffic simulation using real traffic counts gathered in a city. The subsequent simulation is created and analyzed with SUMO traffic simulation package. Traffic congestion is a condition on transport network that occurs as vehicle use increases, and increased vehicular queing. The most common example is the physical use of roads by vehicles. When traffic demand is great enough, the interaction between vehicles slows the speed of the traffic stream. This results in Congestion. Congestion occurs when the capacity of a road is less compared to the volume of traffic. This leads to negative impacts such as Delays, Wasting time of motorists, Inability to forecast travel time accurately, Higher chances of collision of vehicles. To enable smoother flow of traffic, we are developing simulation optimization algorithms for determining the traffic light signal by sensing vehicle density (congestion). The system performance is estimated via SUMO simulation and by using image sensing module of MATLAB/OPEN-CV Software. We perform numerical experiments to test the density of the traffic flow and also compare these results with previous model. To decrease the traffic congestion and avoid the time being wasted by a green light on an empty road.

Other Details

Paper ID: IJSRDV5I41520
Published in: Volume : 5, Issue : 4
Publication Date: 01/07/2017
Page(s): 1723-1726

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