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Technologies of Transit and Mobile Values Implemented in Artificial Intelligence Algorithms that Control Fully Autonomous Driving Vehicles

Technologies of Transit and Mobile Values Implemented in Artificial Intelligence Algorithms that... Empirical research provides mixed results regarding technologies of transit and mobile values implemented in artificial intelligence algorithms that control fully autonomous driving vehicles. Using and replicating data from AUVSI, Capgemini Research Institute, Deloitte, Gallup, Ipsos/GenPop, McKinsey and Co., Perkins Coie, and Statista, I performed analyses and made estimates regarding reasons for choosing an autonomous car at no additional cost over a conventional car (improved fuel efficiency, improved safety, convenience/time saved, and prestige), the ways in which the industry has been affected by recent high-profile problems involving autonomous vehicles, and % of consumers who would be comfortable sharing their personal data with traditional car companies, state authorities responsible for road planning and urban development, technology companies, insurance companies, technology companies that are providing software to traditional car companies, tech startups providing driverless solutions, roadway organizations like privately owned tolling booths, surrounding vehicles, tax authorities, and nearby businesses/businesses on their route. Data were analyzed using structural equation modeling. Keywords: artificial intelligence algorithm; autonomous driving vehicle; mobile value http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Contemporary Readings in Law and Social Justice Addleton Academic Publishers

Technologies of Transit and Mobile Values Implemented in Artificial Intelligence Algorithms that Control Fully Autonomous Driving Vehicles

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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

Empirical research provides mixed results regarding technologies of transit and mobile values implemented in artificial intelligence algorithms that control fully autonomous driving vehicles. Using and replicating data from AUVSI, Capgemini Research Institute, Deloitte, Gallup, Ipsos/GenPop, McKinsey and Co., Perkins Coie, and Statista, I performed analyses and made estimates regarding reasons for choosing an autonomous car at no additional cost over a conventional car (improved fuel efficiency, improved safety, convenience/time saved, and prestige), the ways in which the industry has been affected by recent high-profile problems involving autonomous vehicles, and % of consumers who would be comfortable sharing their personal data with traditional car companies, state authorities responsible for road planning and urban development, technology companies, insurance companies, technology companies that are providing software to traditional car companies, tech startups providing driverless solutions, roadway organizations like privately owned tolling booths, surrounding vehicles, tax authorities, and nearby businesses/businesses on their route. Data were analyzed using structural equation modeling. Keywords: artificial intelligence algorithm; autonomous driving vehicle; mobile value

Journal

Contemporary Readings in Law and Social Justice – Addleton Academic Publishers

Published: Jan 1, 2019

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