Social Internet of Vehicles for Smart Cities

Μαγλαράς, Λέανδρος; Al-Bayatti, Ali H.; He, Ying; Wagner, Isabel; Janicke, Helge

doi:10.3390/jsan5010003

Cited by 138 publications

(74 citation statements)

References 121 publications

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“…The notion of the Social Internet of Vehicles (SIoV) has been well elaborated in [52], [53], towards new contextaware applications involving vehicles, drivers and passengers. The SIoV notion can mean a social network among people in vehicles, or among vehicles themselves, separate from social human networks.…”

Section: A Vehicle-to-vehicle Cooperation and Reasoningmentioning

confidence: 99%

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Loke

2019

IEEE Trans. Intell. Veh.

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The connected automated vehicle has been often touted as a technology that will become pervasive in society in the near future. One can view an automated vehicle as having Artificial Intelligence (AI) capabilities, being able to self-drive, sense its surroundings, recognise objects in its vicinity, and perform reasoning and decision-making. Rather than being stand alone, we examine the need for automated vehicles to cooperate and interact within their socio-cyber-physical environments, including the problems cooperation will solve, but also the issues and challenges. We review current work in cooperation for automated vehicles, based on selected examples from the literature. We conclude noting the need for the ability to behave cooperatively as a form of social-AI capability for automated vehicles, beyond sensing the immediate environment and beyond the underlying networking technology.5 At https://www.sae.org/standardsdev/dsrc/ and in particular the message set dictionary SAE J2735 at https

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Section: A Vehicle-to-vehicle Cooperation and Reasoningmentioning

confidence: 99%

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Loke

2019

IEEE Trans. Intell. Veh.

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“…The growing popularity of the Internet of Things (IoT) enables the communication and interaction of a huge number of devices, which also emphasizes the significance of sensors. Meanwhile, other specific networks—such as the Internet of Vehicles (IoV) [3]—are also growing rapidly, with extraordinary applications such as health care [4] and multimedia [5]. Wearable devices and other personal sensors (including smart vehicles) record our daily data, making the environment of the Social Internet of Things (SIoT) [6] and Social Internet of Vehicles (SIoV) [7] when online social networks (OSNs) are combined.…”

Section: Introductionmentioning

confidence: 99%

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

Zhang

Song

Zhang

et al. 2016

Sensors

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Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management.

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“…However, limited papers have been suggested to bridge SNs and VNs so far. In [9] the concepts have been presented for bridging both SNs and VNs. Maglaras, L.A. and et al have discussed privacy and security issues of the new multidisciplinary research direction.…”

Section: Bridging Sns and Vnsmentioning

confidence: 99%

Grouping vehicles in Vehicular Social Networks

Mahdi

Hasson

2017

KJAR

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As vehicles have become intelligent objects, creating social friendships among them is justifiable. Internet of Vehicles (IoVs) and Vehicular Ad-hoc NETworks (VANETs) are associated terms that are recently highlighted to improve the transportation systems. Intelligent vehicles that can communicate with each other are the main component of vehicular networks (VNs). Indeed, they have resources for that intelligence: CPU, transceiver, sensors and memory. On the other side, social networks (SNs) are also brought to light to mainly study the human relationships. In this context, gathering these vehicles in social groups is reasonable to share their information by bridging VN and SN in a multidisciplinary research direction called vehicular social networks (VSNs).This paper will present a model to group vehicles in two types of social groups. Casual groups and permanent or formal groups will be discussed to increase social ties among vehicles that have the same interests. The results will be analyzed to clarify the most important factors that affect such these relationships.

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Social Internet of Vehicles for Smart Cities

Cited by 138 publications

References 121 publications

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

Grouping vehicles in Vehicular Social Networks

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