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Connected Vehicle Technologies, Autonomous Driving Perception Algorithms, and Smart Sustainable Urban Mobility Behaviors in Networked Transport Systems

Connected Vehicle Technologies, Autonomous Driving Perception Algorithms, and Smart Sustainable... The aim of this paper is to synthesize and analyze existing evidence on connected vehicle technologies, autonomous driving perception algorithms, and smart sustainable urban mobility behaviors in networked transport systems. Using and replicating data from AAA, Abraham et al. (2017), Adobe Analytics, ANSYS, Atomik Research, AUDI AG, AUVSI, Capgemini, CarGurus, CBS Interactive, Ipsos, Nvidia, Perkins Coie, Pew Research Center, TechRepublic, and ZDNet, we performed analyses and made estimates regarding how routing and navigating decisions generated by automated collision avoidance systems across urban driving environments and networked digital infrastructures are optimized by connected vehicle technologies, predictive analytics, and big data-enabled visual perception and recognition. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. Keywords: smart sustainable urban mobility behavior; connected vehicle technology; networked transport system; perception algorithm; autonomous driving http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Contemporary Readings in Law and Social Justice Addleton Academic Publishers

Connected Vehicle Technologies, Autonomous Driving Perception Algorithms, and Smart Sustainable Urban Mobility Behaviors in Networked Transport Systems

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1948-9137
eISSN
2162-2752
Publisher site
See Article on Publisher Site

Abstract

The aim of this paper is to synthesize and analyze existing evidence on connected vehicle technologies, autonomous driving perception algorithms, and smart sustainable urban mobility behaviors in networked transport systems. Using and replicating data from AAA, Abraham et al. (2017), Adobe Analytics, ANSYS, Atomik Research, AUDI AG, AUVSI, Capgemini, CarGurus, CBS Interactive, Ipsos, Nvidia, Perkins Coie, Pew Research Center, TechRepublic, and ZDNet, we performed analyses and made estimates regarding how routing and navigating decisions generated by automated collision avoidance systems across urban driving environments and networked digital infrastructures are optimized by connected vehicle technologies, predictive analytics, and big data-enabled visual perception and recognition. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. Keywords: smart sustainable urban mobility behavior; connected vehicle technology; networked transport system; perception algorithm; autonomous driving

Journal

Contemporary Readings in Law and Social JusticeAddleton Academic Publishers

Published: Jan 1, 2021

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