Investigating Value of Information in Future Vehicular Communications
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Abstract (arXiv)
The next generations of vehicles are expected to be equipped with sophisticated sensors to support advanced automotive services. The large volume of data generated by such applications will likely put a strain on the vehicular communication technologies, which may be unable to guarantee the required quality of service. In this scenario, it is fundamental to assess the value of information (VoI) provided by each data source, to prioritize the transmissions that have greatest importance for the target applications. In this paper, we characterize VoI in future vehicular networks, and investigate efficient data dissemination methods to tackle capacity issues. Through a simulation study, we show how analytic hierarchy multicriteria decision processes can be exploited to determine the value of sensory observations as a function of space, time, and quality criteria.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Jul 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 2.
4 papers.
- 2021On the Role of Sensor Fusion for Object Detection in Future Vehicular Networkscited by 6
- 2022Artificial Intelligence in Vehicular Wireless Networks: A Case Study Using ns-3cited by 3
- 2025Learning Value of Information towards Joint Communication and Control in 6G V2Xcited by 0
- 2025PRATA: A Framework to Enable Predictive QoS in Vehicular Networks via Artificial Intelligencecited by 0
- 2025PRATA: A Framework to Enable Predictive QoS in Vehicular Networks via Artificial Intelligence15 Jul 2025
- 2025Learning Value of Information towards Joint Communication and Control in 6G V2X11 May 2025
- 2022Artificial Intelligence in Vehicular Wireless Networks: A Case Study Using ns-310 Mar 2022
- 2021On the Role of Sensor Fusion for Object Detection in Future Vehicular Networks23 Apr 2021