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/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 Justice – Addleton Academic Publishers
Published: Jan 1, 2021