Urban Mobility Technologies, Algorithm-driven Sensing Devices,
and Machine Learning-based Ethical Judgments in a Connected
Vehicle Environment

J 2020

Urban Mobility Technologies, Algorithm-driven Sensing Devices, and Machine Learning-based Ethical Judgments in a Connected Vehicle Environment

WALKER, Amanda, Zuzana ROWLAND, Katarina FRAJTOVÁ MICHALÍKOVÁ and Lucia ŠVÁBOVÁ

Basic information

Original name

Urban Mobility Technologies, Algorithm-driven Sensing Devices, and Machine Learning-based Ethical Judgments in a Connected Vehicle Environment

Name in Czech

Technologie městské mobility, snímací zařízení řízená algoritmy a etické úsudky založené na strojovém učení v prostředí propojeného vozidla

Authors

WALKER, Amanda (guarantor), Zuzana ROWLAND (203 Czech Republic, belonging to the institution), Katarina FRAJTOVÁ MICHALÍKOVÁ (703 Slovakia) and Lucia ŠVÁBOVÁ (703 Slovakia)

Edition

Contemporary Readings in Law and Social Justice, New York, USA, Addleton Academic Publishers, 2020, 1948-9137

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

50200 5.2 Economics and Business

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

RIV identification code

RIV/75081431:_____/20:00001892

Organization unit

Institute of Technology and Business in České Budějovice

DOI

http://dx.doi.org/10.22381/CRLSJ12220204

Keywords (in Czech)

město; mobilita; algoritmus; strojové učení; propojení; automobily

Keywords in English

urban; mobility; algorithm; machine learning; connected; vehicle

Abstract

ORIG CZ

V originále

Authors develop a conceptual framework based on a systematic and comprehensive literature review on urban mobility technologies. Building their argument by drawing on data collected from AUDI AG, AUVSI, Brookings, Capgemini, CivicScience, Ipsos, Kennedys, Perkins Coie, and Pew Research Center, authors performed analyses and made estimates regarding algorithm-driven sensing devices and machine learning-based ethical judgments in a connected vehicle environment.

In Czech

Autoři vyvíjí koncepční rámec založený na systematickém a komplexním přehledu literatury o technologiích městské mobility. Na základě jejich argumentu čerpáním z údajů shromážděných od AUDI AG, AUVSI, Brookings, Capgemini, CivicScience, Ipsos, Kennedys, Perkins Coie a Pew Research Center autoři provedli analýzy a odhady týkající se snímacích zařízení řízených algoritmy a etické úsudky založené na strojovém učení v prostředí propojeného vozidla.

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Citovat

WALKER, Amanda, Zuzana ROWLAND, Katarina FRAJTOVÁ MICHALÍKOVÁ and Lucia ŠVÁBOVÁ. Urban Mobility Technologies, Algorithm-driven Sensing Devices, and Machine Learning-based Ethical Judgments in a Connected Vehicle Environment. Contemporary Readings in Law and Social Justice. New York, USA: Addleton Academic Publishers, 2020, vol. 12, No 2, p. 34-42. ISSN 1948-9137. Available from: https://dx.doi.org/10.22381/CRLSJ12220204.

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   keywords = {urban; mobility; algorithm; machine learning; connected; vehicle},
   language = {eng},
   issn = {1948-9137},
   journal = {Contemporary Readings in Law and Social Justice},
   title = {Urban Mobility Technologies, Algorithm-driven Sensing Devices, and Machine Learning-based Ethical Judgments in a Connected Vehicle Environment},
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   volume = {12},
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JF  - Contemporary Readings in Law and Social Justice
VL  - 12
IS  - 2
SP  - 34-42
EP  - 34-42
PB  - Addleton Academic Publishers
SN  - 19489137
KW  - urban
KW  - mobility
KW  - algorithm
KW  - machine learning
KW  - connected
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N2  - Authors develop a conceptual framework based on a systematic and comprehensive literature review on urban mobility technologies. Building their argument by drawing on data collected from AUDI AG, AUVSI, Brookings, Capgemini, CivicScience, Ipsos, Kennedys, Perkins Coie, and Pew Research Center, authors performed analyses and made estimates regarding algorithm-driven sensing devices and machine learning-based ethical judgments in a connected vehicle environment.
ER  -

WALKER, Amanda, Zuzana ROWLAND, Katarina FRAJTOVÁ MICHALÍKOVÁ and Lucia ŠVÁBOVÁ. Urban Mobility Technologies, Algorithm-driven Sensing Devices, and Machine Learning-based Ethical Judgments in a Connected Vehicle Environment. \textit{Contemporary Readings in Law and Social Justice}. New York, USA: Addleton Academic Publishers, 2020, vol.~12, No~2, p.~34-42. ISSN~1948-9137. Available from: https://dx.doi.org/10.22381/CRLSJ12220204.

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