Using Case-Based Reasoning for Intelligent Time of Arrival Estimation

Abstract: Traffic congestion and over saturation is a common worldwide problem. This problem is more severe in urban areas due to rapid increase in number of vehicles. City traffic often results in traffic blockage at peak office hours. The same situation can also be observed on freeways, especially at entrance/exit areas of a city. In most cases the drivers are totally unaware about road traffic situations in advance. Intelligent transportation systems offer various applications to improve road traffic.  In this manner the timely and reliable traffic information can be greatly beneficial for travelers. Real time travel time information can be adopted by vehicles as an excellent tool which can result to reduce the impact of continuous traffic increase on urban roads. Real time travel time estimation is a complex task as it involves various factors. This travel time estimation is even more difficult for urban road networks. In our dissertation, we have investigated an estimated time of arrival approach in order to inform the drivers in advance about travel time. We have introduced Estimated Time of Arrival (ETA) in a clever and intelligent fashion by developing a Case-Based Reasoning engine. We believe that by adopting this simple and intelligent approach, it can greatly help improving traffic congestion overall. We also believe that this strategy will also help in reducing the emission of environment unfriendly gases, thus helping mankind.