Autonomous Vehicle Decision-Making Algorithms and Data-driven Mobilities in Networked Transport Systems
Edward TaylorABSTRACT. This article presents an empirical study carried out to evaluate and analyze autonomous vehicle decision-making algorithms and data-driven mobilities in networked transport systems. Building my argument by drawing on data collected from AAA, Accenture, ANSYS, APA, Atomik Research, AUVSI, BikePGH, Black & Veatch, Brookings, CARiD, eMarketer, MRCagney, Perkins Coie, and Pew Research Center, I performed analyses and made estimates regarding Internet of Things-assisted smart logistics transportation. Data collected from 5,400 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
Keywords: networked transport system; autonomous vehicle; data-driven mobility
How to cite: Taylor, E. (2021). “Autonomous Vehicle Decision-Making Algorithms and Data-driven Mobilities in Networked Transport Systems,” Contemporary Readings in Law and Social Justice 13(1): 9–19. doi: 10.22381/CRLSJ13120211.
Received 12 March 2021 • Received in revised form 10 July 2021
Accepted 13 July 2021 • Available online 15 July 2021