ROWLAND, Zuzana and Kathleen PORTER. Autonomous vehicle driving algorithms, deep learning-based sensing technologies, and big geospatial data analytics in smart sustainable intelligent transportation systems. Contemporary Readings in Law and Social Justice. New York, USA: Addleton Academic Publishers, vol. 13, No 2, p. 23-36. ISSN 1948-9137. 2021.
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Basic information
Original name Autonomous vehicle driving algorithms, deep learning-based sensing technologies, and big geospatial data analytics in smart sustainable intelligent transportation systems
Authors ROWLAND, Zuzana (203 Czech Republic, guarantor, belonging to the institution) and Kathleen PORTER.
Edition Contemporary Readings in Law and Social Justice, New York, USA, Addleton Academic Publishers, 2021, 1948-9137.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 50200 5.2 Economics and Business
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/75081431:_____/21:00002226
Organization unit Institute of Technology and Business in České Budějovice
Keywords in English autonomous vehicle; deep learning; driving algorithm; intelligent transportation system; big data; geospatial analytics
Tags BSA_MIE, RIV21, SCOPUS
Changed by Changed by: Mgr. Nikola Petříková, učo 28324. Changed: 16/12/2021 14:43.
Abstract
"The authors draw on a substantial body of theoretical and empirical research on autonomous vehicle driving algorithms, deep learning-based sensing technologies, and big geospatial data analytics in smart sustainable intelligent transportation systems, and to explore this, they inspect, use, and replicate survey data from AUVSI, BikePGH, Capgemini, CarGurus, CivicScience, GenPop, Ipsos, KPMG, Management Events, McKinsey, Perkins Coie, Pew Research Center, and Statista."
PrintDisplayed: 29/3/2024 15:36