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Autonomous Driving Algorithms and Behaviors, Sensing and Computing Technologies, and Connected Vehicle Data in Smart Transportation Networks

Autonomous Driving Algorithms and Behaviors, Sensing and Computing Technologies, and Connected... This article presents an empirical study carried out to evaluate and analyze autonomous driving algorithms and behaviors, sensing and computing technologies, and connected vehicle data in smart transportation networks. Building our argument by drawing on data collected from AAA, AUVSI, CARiD, Deloitte, McKinsey, Perkins Coie, Schoettle and Sivak (2014), Statista, Thomas et al. (2015), and YouGov, we performed analyses and made estimates regarding how autonomous vehicle planning and driving algorithms can optimize road safety, being instrumental in sensor and data processing methods by cutting down crashes and casualties through a massive volume of information that can be shared between selfdriving cars and roadside infrastructure. Data collected from 5,900 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. Keywords: sensing and computing technology; autonomous driving; smart transportation network; connected vehicle data; algorithm; behavior http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Contemporary Readings in Law and Social Justice Addleton Academic Publishers

Autonomous Driving Algorithms and Behaviors, Sensing and Computing Technologies, and Connected Vehicle Data in Smart Transportation Networks

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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 presents an empirical study carried out to evaluate and analyze autonomous driving algorithms and behaviors, sensing and computing technologies, and connected vehicle data in smart transportation networks. Building our argument by drawing on data collected from AAA, AUVSI, CARiD, Deloitte, McKinsey, Perkins Coie, Schoettle and Sivak (2014), Statista, Thomas et al. (2015), and YouGov, we performed analyses and made estimates regarding how autonomous vehicle planning and driving algorithms can optimize road safety, being instrumental in sensor and data processing methods by cutting down crashes and casualties through a massive volume of information that can be shared between selfdriving cars and roadside infrastructure. Data collected from 5,900 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. Keywords: sensing and computing technology; autonomous driving; smart transportation network; connected vehicle data; algorithm; behavior

Journal

Contemporary Readings in Law and Social Justice – Addleton Academic Publishers

Published: Jan 1, 2021

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