mini project
abstract:
Traffic control systems play an important role to manage traffic congestion on the road especially during peak hours and peak seasons. One of the main challenges is to control the traffic when there are emergency cases at traffic light intersections, especially peak hours. This could affect the route for emergency vehicles such as ambulances, fire brigade and police cars to reach their destination. Due to the increase of traffic congestion during peak hours and peak seasons in Malaysia, there is a need for further evaluation of traffic control techniques. This paper reviewed and consolidated information on the different types of the existing traffic control system for road traffic management such as OpenCV and image processing. This paper analysed and compared the design, benefits and limitations of each technique. Through the reviews, this paper recommends the best traffic control technique for emergency vehicles that offers low price, low maintenance and can be used in various areas of applications.
RESULT:
-> Traffic congestion can be solved. -> Emergency vehicles can reach the destination earliest. -> Traffic density is continuously monitor by video processing and converted into frames. -> The frames are analyzed by various techniques of image processing they are segmented for distinguish between ambulance and other vehicles. -> Traffic signals continuously glow to green as long as emergency vehicle is passed through the traffic and it is allowed to reach its destination.
Conclusion:
By this project the problem of traffic can be easily sorted out: the timing of each signal can be automatically adjusted according to density of traffic which is real time operation. It will also clear the path for the ambulance, fire brigade in emergency cases and also it will help to public in taking decisions for reaching their destination in time using auto-routing method. It shows that it can reduce the traffic congestion and avoids the time being wasted by a greenlight on an empty road. It is also more consistent in detecting vehicle presence because it uses actual traffic images. It visualizes the reality so it functions much better than those systems that rely on the detection of the vehicles metal content. Overall, the system is good but it still needs improvement to achieve a hundred percent accuracy.