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Big Data-driven Governance of Smart Sustainable Intelligent Transportation Systems: Autonomous Driving Behaviors, Predictive Modeling Techniques, and Sensing and Computing Technologies

Big Data-driven Governance of Smart Sustainable Intelligent Transportation Systems: Autonomous... This article reviews and advances existing literature concerning computer vision and route planning algorithms, sensing and computing technologies, and vehicle and pedestrian detection tools. Throughout June 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “big data-driven governance” + “smart sustainable intelligent transportation systems” + “autonomous driving behaviors,” “predictive modeling techniques,” and “sensing and computing technologies.” As research published in 2022 was inspected, only 181 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 37 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR. Keywords: smart sustainable intelligent transportation system; autonomous driving behavior; predictive modeling technique; sensing and computing technology http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Contemporary Readings in Law and Social Justice Addleton Academic Publishers

Big Data-driven Governance of Smart Sustainable Intelligent Transportation Systems: Autonomous Driving Behaviors, Predictive Modeling Techniques, and Sensing and Computing Technologies

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1948-9137
eISSN
2162-2752
Publisher site
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Abstract

This article reviews and advances existing literature concerning computer vision and route planning algorithms, sensing and computing technologies, and vehicle and pedestrian detection tools. Throughout June 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “big data-driven governance” + “smart sustainable intelligent transportation systems” + “autonomous driving behaviors,” “predictive modeling techniques,” and “sensing and computing technologies.” As research published in 2022 was inspected, only 181 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 37 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR. Keywords: smart sustainable intelligent transportation system; autonomous driving behavior; predictive modeling technique; sensing and computing technology

Journal

Contemporary Readings in Law and Social Justice – Addleton Academic Publishers

Published: Jan 1, 2022

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