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Title: Predicting Vehicular Collisions in Vehicle-to-vehicle Networks using Physical Layer Techniques
Committee:
Dr. John Copeland, ECE, Advisor, Chair , Advisor
Dr. George Riley, ECE
Dr. Gregory Durgin, ECE
Dr. Raheem Beyah, ECE
Dr. Ellen Zegura, CoC
Dr. Yusun Chang, ECE
Abstract:
This dissertation presents novel physical layer (PHY) techniques for providing collision avoidance services to drivers and future autonomous systems participating in Vehicle-to-Vehicle (V2V) networks. To date, predicting car collisions by observing PHY characteristics of DSRC radios in V2V networks is not well investigated nor validated. The periodic broadcast of either SM or non-safety network traffic could be leveraged to identify physically observable events indicative of a collision. The advancements presented in this work will allow future investigators the opportunity to design new collision avoidance methods and to develop additional services for both drivers and autonomous systems. With this body of work, car accidents could be reduced and V2V enhanced to provide collision avoidance not just at the application layer, but directly from the PHY of the communication stack.
