Internet of vehicles: From intelligent grid to autonomous cars and vehicular clouds

By Mario Gerla, Eun-Kyu Lee, Giovanni Pau, Uichin Lee. 2014

534 citations recorded by the source corpus.

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.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

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Citations in the corpus

A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019, background): “4) Connected systems: There is no operational connected ADS in use yet, however, some researchers [44]–[46] be-”
A survey of attacks and detection mechanisms on intelligent transportation systems: VANETs and IoV (2017, background): “For example, an attack which spoofs GPS information or disables the steering or braking system in an autonomous vehicle could be extremely dangerous [13].”
Federated Learning in Smart City Sensing: Challenges and Opportunities (2020, unknown): “The development of Internet of Vehicles (IoV) and Road Networking technologies will propel autonomous vehicles to become a technological direction with extremely high social value and economic value [166].”
Software defined networking-based vehicular Adhoc Network with Fog Computing (2015, background): “Moreover, the rapid development of cloud computing soon paves the way to a further step of the Vehicle Cloud in which provides all kinds of cloud service to the transportation [31].”
A Complex View of Industry 4.0 (2016, background): “According to previously stored data, the smart key can also set the positions of the seat and steering wheel, and start the car when the driver is behind the wheel (Gerla, Lee, Pau, & Lee, 2014).”
A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues (2020, background): “Since build-in proactive urban monitoring solutions like MobEyes [81] or Pics-on-Wheels [85] record the surroundings while driving, forensics professionals could even search the vehicular network for video material of the accident.”
From Cloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework (2017, background): “[119] described a vehicular fog as the equivalent of Internet cloud in vehicles and the core system environment that will enhance autonomous driving.”
CoEdge: Cooperative DNN Inference With Adaptive Workload Partitioning Over Heterogeneous Edge Devices (2020, unknown): “factory [2], autonomous driving [3], etc.”
Consumer and Object Experience in the Internet of Things: An Assemblage Theory Approach (2018, background): “Platooning strategies of autonomous vehicles represent agentic (leader) and communal (collaborative and follower) behaviors (Fernandes and Nunes 2012; Gerla et al. 2014).”
Internet of things security: A top-down survey (2018, background): “Connected vehicles are becoming more important with the aim to make driving more reliable, enjoyable and e ﬃ cient [50].”