Real-World Connected Vehicle Data, Deep Learning-based Sensing Technologies, and Decision-Making Self-Driving Car Control Algorithms in Autonomous Mobility Systems
Carol WelchABSTRACT. 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.
Keywords: autonomous mobility; connected vehicle data; control algorithm; sensor
How to cite: Welch, C. (2021). “Real-World Connected Vehicle Data, Deep Learning-based Sensing Technologies, and Decision-Making Self-Driving Car Control Algorithms in Autonomous Mobility Systems,” Contemporary Readings in Law and Social Justice 13(1): 81–90. doi: 10.22381/CRLSJ13120218.
Received 20 March 2021 • Received in revised form 6 July 2021
Accepted 12 July 2021 • Available online 15 July 2021
