Urban Mobility Technologies, Algorithm-driven Sensing Devices, and Machine Learning-based Ethical Judgments in a Connected Vehicle Environment
Urban Mobility Technologies, Algorithm-driven Sensing Devices, and Machine Learning-based Ethical Judgments in a Connected Vehicle Environment
Author(s): Amanda Walker, Zuzana Rowland, Katarina Frajtova Michalikova, Lucia SvabovaSubject(s): Rural and urban sociology, Transport / Logistics
Published by: Addleton Academic Publishers
Keywords: urban; mobility; algorithm; machine learning; connected;vehicle age;
Summary/Abstract: We develop a conceptual framework based on a systematic and comprehensive literature review on urban mobility technologies. Building my argument by drawing on data collected from AUDI AG, AUVSI, Brookings, Capgemini, CivicScience, Ipsos, Kennedys, Perkins Coie, and Pew Research Center, we performed analyses and made estimates regarding algorithm-driven sensing devices and machine learning-based ethical judgments in a connected vehicle environment. The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 5,200 respondents.
Journal: Contemporary Readings in Law and Social Justice
- Issue Year: 12/2020
- Issue No: 2
- Page Range: 34-42
- Page Count: 9
- Language: English
- Content File-PDF