Smart Vehicular communication for Road status analysis and Vehicle trajectory prediction

摘要

In this paper, our perspective on Vehicular communication is described smartly. There are multiple challenges due to high dynamics in the vehicular environment. Wireless network, while evolving towards high mobility provide better support for the connected Vehicles, which also motivates the traditional wireless designs of on-board sensors in the vehicles that generates a large volume of data continuously. Our paper focuses on Mobility networks where vehicles communicate with Road Side Unit (RSU) to form Vehicular Ad-hoc Network (VANET) and have a safe commute. Using Machine Learning algorithm like SVM an accurate Vehicular trajectory prediction method has been designed and have devised methods for Road Status Analysis, Pothole detection and used SHA-1 algorithm for secured exchange of information between RSU and vehicles. In our experimental setup, Smartphones are used as vehicles, which gets connected to a stationery System acting as RSU through a data hotspot and receive messages about road conditions and peer-vehicles trajectory. In the real world scenario of Vehicular communication, there is a need for more storage, high-speed data connectivity and Intelligent vehicles. This challenge can be rightly met by utilizing the technologies like data Cloud for large database storage, 5G connectivity and ML/DL techniques.