Real-World Connected Vehicle Data, Deep Learning-based Sensing Technologies, and Decision-Making Self-Driving Car Control Algorithms in Autonomous Mobility Systems
Real-World Connected Vehicle Data, Deep Learning-based Sensing Technologies, and Decision-Making Self-Driving Car Control Algorithms in Autonomous Mobility Systems

Summary/Abstract: The purpose of this study was to empirically examine real-world connected vehicle data, deep learning-based sensing technologies, and decision-making self-driving car control algorithms in autonomous mobility systems. Building my argument by drawing on data collected from AAA, Abraham et al. (2017), ANSYS, Atomik Research, AUVSI, Brookings, CivicScience, Deloitte, EY, HNTB, Ipsos, Kennedys, McKinsey, Perkins Coie, SAE, and Schoettle & Sivak (2014), I performed analyses and made estimates regarding the level of connected and autonomous vehicle adoption. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

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