Internet of vehicles: From intelligent grid to autonomous cars and vehicular clouds
Open accessAbstract
Traditionally, the vehicle has been the extension of the man's ambulatory system, docile to the driver's commands. Recent advances in communications, controls and embedded systems have changed this model, paving the way to the Intelligent Vehicle Grid. The car is now a formidable sensor platform, absorbing information from the environment (and from other cars) and feeding it to drivers and infrastructure to assist in safe navigation, pollution control and traffic management. The next step in this evolution is just around the corner: the Internet of Autonomous Vehicles. Pioneered by the Google car, the Internet of Vehicles will be a distributed transport fabric capable to make its own decisions about driving customers to their destinations. Like other important instantiations of the Internet of Things (e.g., the smart building), the Internet of Vehicles will have communications, storage, intelligence, and learning capabilities to anticipate the customers' intentions. The concept that will help transition to the Internet of Vehicles is the Vehicular Cloud, the equivalent of Internet cloud for vehicles, providing all the services required by the autonomous vehicles. In this article, we discuss the evolution from Intelligent Vehicle Grid to Autonomous, Internet-connected Vehicles, and Vehicular Cloud.
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VANETs can be realized in two different ways: conventional IP based networking and Information-Centric Networking (ICN).
“VANETs can be realized in two different ways: conventional IP based networking and Information-Centric Networking (ICN) [48].”
From A Survey of Autonomous Driving: <i>Common Practices and Emerging Technologies</i> (2020) · cites this paper as [48]
The increasing popularity of ML risks non-domain experts unintentionally misusing datasets that are unsuitable in particular contexts.
“the increasing popularity of ML risks those who are not domain experts unintentionally misusing datasets which are unsuitable in particular contexts [38]”
From Decision Provenance: Harnessing Data Flow for Accountable Systems (2019) · cites this paper as [38]
It is increasingly recognised that ML practitioners should record information relating to datasets, such as motivation for creation, composition, collection, preprocessing, distribution, maintenance, and legal and ethical considerations.
“It is increasingly recognised the importance for the ML practitioners, themselves, to record information relating to the datasets, such as their motivation for creation, composition, process of collection, preprocessing, distribution, maintenance, and legal and ethical considerations [38].”
From Decision Provenance: Harnessing Data Flow for Accountable Systems (2019) · cites this paper as [38]
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- Authors
- Gerla, M., Lee, E.-K., Pau, G., & Lee, U.
- Affiliations
- University of California, Los Angeles (US)
- Korea Advanced Institute of Science and Technology (KR)
- Venue
- 2014 IEEE World Forum on Internet of Things (WF-IoT)
- Publisher
- IEEE
- Published
- 2014-03
- Pages
- 241-246
- OpenAlex
- W2137693329
- Cited by
- 828
- References
- 13
- Citations by year
- 2026: 20 · 2025: 31 · 2024: 36 · 2023: 40 · 2022: 53 · 2021: 90 · 2020: 103 · 2019: 118 · 2018: 138 · 2017: 98 · 2016: 64 · 2015: 31 · 2014: 5 · 2013: 1
- FWCI
- 80.26
- Type
- conference paper
- Language
- en
- Open access
- green
- hal.science
- Licence
- cc-by-nc
- Locations
- IEEE World Forum on Internet of Things (WF-IoT) (publishedVersion)
- HAL (submittedVersion, cc-by-nc)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- Internet of Vehicles, autonomous vehicles, vehicular cloud computing, Internet of Things, vehicle-to-vehicle communication, vehicle-to-infrastructure communication, connected vehicles, traffic management
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