Taxi Demand Prediction using L-CNN

Abstract

In transportation, taxi demand is a main issue in urban communities especially during the peak time. So there is a strong need for taxi prediction framework to satisfy the passenger's request. This framework assigns the taxi based on the waiting time, clients and place such as airport, hospital, school, railway station who use the taxi repeatedly on time for same destination. Usually the prediction framework depends on the bustling region which all the framework does. For making the trust between the drivers and clients the structure needs a qualified prediction framework. In the proposed framework foreseeing the specific feature by utilizing the look-up convolutional neural network system (LCNN).Finally, clustering the information depend on precipitation for qualified candidates who utilizes the framework recursively. As the outcomes shows the developed prediction framework accomplishes better execution and make a trust connection between the users and the drivers at the same time.