RESULTS AND DISCUSSIONExperimental

RESULTS AND DISCUSSIONExperimental results: Aimsun is the platform which has been developed to improve the transportation system. This platform has been used to evaluate tlie performance.It also gives the information about traffic present on road in percentage. To check the performance of proposed framework, Aimsun simulation test bed has been used as shown in Fig. 7. In GUI '+，type road has made with vision sensors to check the variations in timing of red/green lights. Figure 8 Shows the two images captured at different projections. After processing these images, final mosaicked image is shown in Fig. 9.To compare proposed technique with conventional techniques, an experiment has been performed on one vehicle. One of the vehicles is allowed to go to in W-E direction at 20 km h-1 on Aim sun test bed. Total time of 300 seconds is given to vehicle to check the distance to be covered. Randomly, traffic density is applied on road to check the performance. The same conditions have been applied to ANN with conventional sensors technique to check their performances. After simulate the experiment, it is found that vehicle when adopt Neural Network controller with Vision Sensor (NNVS) computing, covers 600 m distance in specified time period whereas distance covered by vehicle using technique ANN with conventional sensor is 480 m. Simulation results shows average waiting time and moving times for vehicles