A traffic alert system that uses poisson probability distribution to predict the likelihood of traffic congestion along Wandegeya streets

Abstract

Traffic congestion is the overload of the road network capacity due to increased traffic volume or interruptions on the roads causing increase in travel time. While traffic congestion is being experienced in all biggest cities of the world, it is more severe and difficult to mitigate in cities of the developing world countries like Kampala. The main objective of the study was to provide a solution that enables road users to avoid traffic congestion along the streets of Wandegeya by using probability theory. Through observation data collection method, data was collected on about the traffic flow along the streets next to Wandegeya round about, analysed from which the traffic flow patterns were obtained. The traffic follow patterns were found to follow a Poisson probability distribution which was used to predict the chances of traffic congestion along a given street within a specified time interval and an algorithm was formed. A summary was obtained for the algorithm and presented on a website developed using wordpress.com which the researcher highly recommends since it provided a solution to avoiding traffic congestion. To improve the system, live environment or real time data collection equipment for example CCTV cameras, GPS sensors and others can be adjusted onto the system to collect and provide a solution in case of unprecedented events and happening at the junction