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The Algorithmic Governance of Connected Autonomous Vehicles: Data-driven Decision Support Systems and Smart Sustainable Urban Mobility Behaviors

The Algorithmic Governance of Connected Autonomous Vehicles: Data-driven Decision Support Systems and Smart Sustainable Urban Mobility Behaviors

ABSTRACT. I draw on a substantial body of theoretical and empirical research on the algorithmic governance of connected autonomous vehicles, and to explore this, I inspected, used, and replicated survey data from AAA, ANSYS, Atomik Research, AUVSI, BCG, Brookings, Capgemini, CivicScience, GenPop, Ipsos, Perkins Coie, Statista, and World Economic Forum, performing analyses and making estimates regarding data-driven decision support systems and smart sustainable urban mobility behaviors. Structural equation modeling was used to analyze the data and test the proposed conceptual model.

Keywords: urban mobility; connected; autonomous; vehicle; smart; sustainable

How to cite: Davidson, R. (2020). “The Algorithmic Governance of Connected Autonomous Vehicles: Data-driven Decision Support Systems and Smart Sustainable Urban Mobility Behaviors,” Contemporary Readings in Law and Social Justice 12(2): 16–24. doi:10.22381/CRLSJ12220202

Received 9 June 2020 • Received in revised form 6 November 2020
Accepted 8 November 2020 • Available online 10 November 2020

Robert Davidson
r.davidson@aa-er.org
The Center for Digital Labor Markets
at CLI, Sydney, Australia