D2VNet 2020, ACM MobiHoc Workshop on Cooperative data dissemination in future vehicular networks, in conjunction with MOBIHOC 2020, October 11–14, 2020, Boston, MA, USA
Vehicles are expected to generate and consume an increasing amount of data, but how to perform risk reasoning over relevant data is still not yet solved. Location, time of day and driver behavior change the risk dynamically and make risk assessment challenging. This
paper introduces a new paradigm, transferring information from raw sensed data to knowledge and explores the knowledge of risk reasoning through vehicular maneuver conflicts. In particular, we conduct a simulation study to analyze the driving data and extract the knowledge of risky road users and risky locations. We use knowledge to facilitate reduced volume and share it through a Vehicular Knowledge Network (VKN) for better traffic planning and safer driving.
Type:
Conférence
City:
Boston
Date:
2020-10-11
Department:
Systèmes de Communication
Eurecom Ref:
6320
Copyright:
© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in D2VNet 2020, ACM MobiHoc Workshop on Cooperative data dissemination in future vehicular networks, in conjunction with MOBIHOC 2020, October 11–14, 2020, Boston, MA, USA https://doi.org/10.1145/3397166.3413467
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