Mobility Prediction in Vehicular Ad-Hoc Networks: Prediction Aims, Techniques, Use Cases, and Research Challenges

Abstract

The accurate prediction of the vehicle mobility in Vehicular Ad-hoc Networks (VANETs) has a significant effect in the rapid deployment of Intelligent Transport Systems (ITSs) as well as in building efficient vehicular communication protocols. Thus, this article aims to briefly review the contemporary research progress in the field of mobility prediction in VANETs. The fundamental objective here is to explore the major mobility prediction aims, techniques, and use cases in VANETs, with focusing on the prerequisites, advantages, and limitations. Furthermore, performance and usage analysis are presented with the aim to deduce the appropriateness of utilizing each prediction aim/technique for the varied use cases. Finally, the relevant research challenges are identified to shape the future of the mobility prediction in VANETs. A thorough knowledge and understanding of the mobility prediction are provided, with the aim of enhancing the robustness and reliability of the mobility prediction in VANETs.