GPS-Based Route Choice Model for Smart Transportation System: Bringing Intelligence into Vehicular Cloud

Abstract

An IoT-based intelligent performance evaluation strategy is anticipated to rationalize the communication among the vehicles, manage vehicle traffic, support vehicle drivers with privacy and safety, and provision significant applications for cloud users. GPS-based route choice model is substantial for handling the transportation complications of a big city, traffic engineering, and remote communication among vehicles. With this scenario in mind, we recommend a strategy to manage and evaluate the performance of the vehicular cloud. Different types of cloud services, storage mechanisms, resources, and information management are provided to the cloud users, commercial vehicles, emergency services, and disaster services through the vehicular cloud computing model. The performance of the vehicular cloud can be raised to meet the information requirements of the cloud users by using the proposed route choice model. The primary objective of the proposed model is to provide the finest traffic light control method using GPS inputs and vehicular area networks. An accurate traffic flow approximation method in vehicular area networks is useful to expect the amount of obtainable computational resources within a roadway subdivision given the unplanned arrivals and departures for smart transportation systems by bringing intelligence into the dynamic vehicular cloud.