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/lp/addleton-academic-publishers/connected-vehicle-technologies-autonomous-driving-perception-vK0IzkTATE
- 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 Justice – Addleton Academic Publishers
Published: Jan 1, 2021