Date of Award

7-28-2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Systems Engineering

First Advisor

Seshadri Mohan

Abstract

The field of connected vehicles (CV) stands at the confluence of three evolving disciplines – the Internet of Things (IoT), emerging standards for connectivity of vehicles, and AI/machine learning. CV regarded as a true solution to reduce the number of accidents. in this work conducting a protocol performance road test and applying machine learning algorithms have been investigated. we used Universal Software Radio Peripheral (USRP) N210 devices to build ad hoc Vehicles Network based on IEEE 802.11p protocol and create an application layer using python language to build drowsiness detection system which resolve a significant safety issue nowadays. The application layer has been built based on MAC and Physical layers to deliver a real time drowsiness detection system, which determined the rate of messages that can be transmitted and received in both indoor and outdoor environments. The response time was observed to be around 50 seconds on average. Our aim is to implement DSRC based on IEEE 802.11p protocol so the connected vehicles can share data between themselves in real-time. Besides, we investigate scalability analysis for database traffic rate for IMS -eMBMS (evolved multi broadcast multicast services) servers of CV2X Networks to provide network designers with a vision into size IMS-eMBMS servers that required to support vehicle users by determining the overall load on the cellular system.

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