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ABSTRACT. This article presents an empirical study carried out to evaluate and analyze autonomous vehicle decision-making algorithms and big data-driven transportation networks in smart urbanism. Building my argument by drawing on data collected from AAA, ANSYS, Atomik Research, BCG, Capgemini, Ipsos, Kennedys, Statista, and World Economic Forum, I performed analyses and made estimates regarding uses, benefits, and social implications of autonomous vehicles. Data collected from 4,800 respondents are tested against the research model by using structural equation modeling.

Keywords: urbanism; autonomous; vehicle; decision-making; algorithm; data

How to cite: Green, M. (2020). “Smart Urbanism: Autonomous Vehicle Decision-Making Algorithms and Big Data-driven Transportation Networks,” Contemporary Readings in Law and Social Justice 12(1): 65–71. doi:10.22381/CRLSJ12120209

Received 14 February 2020 • Received in revised form 4 July 2020
Accepted 7 July 2020 • Available online 10 July 2020

Matthew Green
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Health Economics Research Unit
at CLI, Glasgow, Scotland

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