Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Autonomous Vehicle Interaction Control Software, Big Geospatial Data Analytics, and Networked Driverless Technologies in Smart Sustainable Urban Transport Systems

Autonomous Vehicle Interaction Control Software, Big Geospatial Data Analytics, and Networked... The purpose of this study was to empirically examine autonomous vehicle interaction control software, big geospatial data analytics, and networked driverless technologies in smart sustainable urban transport systems. Building our argument by drawing on data collected from ANSYS, APA, Atomik Research, AUDI AG, AUVSI, Brookings, Capgemini, CivicScience, Dentons, Ipsos, and Perkins Coie, we performed analyses and made estimates regarding how automated navigational software, sensor-based traffic flow data, edge computing techniques, computer vision operations through collaborative perception, and collision avoidance technologies configure smart transportation mobility across vehicular networks, shaping the acceptance and adoption of self-driving cars. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. Keywords: autonomous vehicle; urban transport system; big data; geospatial analytics; interaction control software; networked driverless technology http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Contemporary Readings in Law and Social Justice Addleton Academic Publishers

Autonomous Vehicle Interaction Control Software, Big Geospatial Data Analytics, and Networked Driverless Technologies in Smart Sustainable Urban Transport Systems

Loading next page...
 
/lp/addleton-academic-publishers/autonomous-vehicle-interaction-control-software-big-geospatial-data-Mrs3EpLF0Z
Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1948-9137
eISSN
2162-2752
Publisher site
See Article on Publisher Site

Abstract

The purpose of this study was to empirically examine autonomous vehicle interaction control software, big geospatial data analytics, and networked driverless technologies in smart sustainable urban transport systems. Building our argument by drawing on data collected from ANSYS, APA, Atomik Research, AUDI AG, AUVSI, Brookings, Capgemini, CivicScience, Dentons, Ipsos, and Perkins Coie, we performed analyses and made estimates regarding how automated navigational software, sensor-based traffic flow data, edge computing techniques, computer vision operations through collaborative perception, and collision avoidance technologies configure smart transportation mobility across vehicular networks, shaping the acceptance and adoption of self-driving cars. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. Keywords: autonomous vehicle; urban transport system; big data; geospatial analytics; interaction control software; networked driverless technology

Journal

Contemporary Readings in Law and Social JusticeAddleton Academic Publishers

Published: Jan 1, 2021

There are no references for this article.