ABSTRACT. Empirical evidence on autonomous driving perception algorithms and urban mobility technologies in smart transportation systems has been scarcely documented in the literature. The data used for this study was obtained and replicated from previous research conducted by Adobe Analytics, ANSYS, Atomik Research, AUVSI, Brookings, Capgemini, Charles Koch Institute, Deloitte, eMarketer, GenPop, Ipsos, Kennedys, McKinsey, Perkins Coie, Pew Research Center, SAE, and Statista. We performed analyses and made estimates regarding sustainable mobility and urban public transport systems. Data collected from 6,400 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

Keywords: autonomous driving; smart; urban; mobility; perception algorithm

How to cite: Green, L., and Zhuravleva, N. A. (2021). “Autonomous Driving Perception Algorithms and Urban Mobility Technologies in Smart Transportation Systems,” Contemporary Readings in Law and Social Justice 13(1): 71–80. doi: 10.22381/CRLSJ13120217.

Received 27 March 2021 • Received in revised form 10 July 2021
Accepted 12 July 2021 • Available online 15 July 2021

Linda Green
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Cognitive Artificial Intelligence Systems Laboratory
at ISBDA, Cambridge, England
(corresponding author)
Natalia A. Zhuravleva
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Faculty of Economics and Management,
Department of Transport Economics,
Emperor Alexander I St. Petersburg
State Transport University, St. Petersburg, Russia

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