Developing models for managing drones in the transportation system in smart cities

Abstract

Drones have shown applications in different areas including crop yield prediction, land use surveys in rural and urban regions, traffic surveillance and weather research. The applications of drones in the smart city will involve multiple drone platforms that operate simultaneously to run missions. Therefore, a safe and secure environment for drones' operational quality and stability is necessary. The investigation of the drone traffic safety and the development of the intelligent transportation system needs drone-following models, which describes the one-by-one following process of drones in the traffic flow. There are two types of drone-following models that are proposed and discussed in this paper. The first models based on the principle that keeps a safe distance according to relative velocity, which based on the determining of the drone acceleration depending on the differences in speeds and gaps between the given drone and its leading drone. Another model is the Markov drone-following model which is an improved model based on the approximation of the stochastic diffusion process of speed decision. Extensive simulation and comparison have been conducted for evaluation. The results illustrate the validity and effectiveness of the proposed drone-following models.