Machine Learning Techniques for Intelligent Transportation Systems-An overview

in earlier days, people uses foot or animal cart for moving from one place to another. Now days, variety of vehicles are introduced by human being for the different purposes like cycle, bike, car, lorry, bus, truck, Auto-rickshaw etc. In an advanced transportation systems, based on the customer requirements and demands, every new inventor includes new features and facilities in the creations. The purpose of an Intelligent Transportation Systems (ITS) is to provide creative services in the field of transportation management as well as make the users to be more coordinated and safer while using the transport networks. Machine Learning is one of the best tools which help the transport industry to provide smart transportation by collecting all the safety and security related information like driver's behaviors, traffic congestion, collision prediction and warning, V2V connection and V2I connection with the support of various machine learning algorithms and internet of things. In this review paper, different kind of machine learning techniques, steps to implement machine learning algorithms in MATLAB are discussed for an ITS.