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ABSTRACT. Empirical evidence on connected and autonomous transport systems has been scarcely documented in the literature. Using and replicating data from Accenture, AUVSI, Behaviour & Attitudes, Black & Veatch, Capgemini, eMarketer, Kennedys, Morning Consult, Perkins Coie, SAE, Statista, and YouGov, I performed analyses and made estimates regarding deep learning-based sensing technologies, data-driven mobilities, and intelligent vehicular networks. Data were analyzed using structural equation modeling.

Keywords: connected; autonomous; transport; big data; mobility; vehicular network

How to cite: Robinson, R. (2020). “Connected and Autonomous Transport Systems: Deep Learning-based Sensing Technologies, Data-driven Mobilities, and Intelligent Vehicular Networks,” Contemporary Readings in Law and Social Justice 12(2): 52–60. doi:10.22381/CRLSJ12220206

Received 5 June 2020 • Received in revised form 4 November 2020
Accepted 7 November 2020 • Available online 10 November 2020

Rachel Robinson
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Cyber-Physical Production Networks Research Unit
at AAER, Wellington, New Zealand

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