4.7 Article

UAV-Aided Information Diffusion for Vehicle-to-Vehicle (V2V) in Disaster Scenarios

Journal

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
Volume 10, Issue 4, Pages 1909-1917

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TETC.2021.3120551

Keywords

Vehicle-to-vehicle (V2V) communication; intelligent transport system (ITS); information diffusion; unmanned aerial vehicle (UAV)

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Collecting and providing information are crucial for safe driving and automatic operation in intelligent transport systems (ITSs). When disasters occur, UAVs can assist in spreading information uninterruptedly and contribute to managing traffic situations through vehicle-to-vehicle communication.
To support safe driving and automatic operation, collecting and providing information are important in intelligent transport systems (ITSs). Information and communication technology utilization is needed even when disasters occur because it is possible to collect and analyze vehicle position information via roadside units and thus locate accidents and traffic jams. However, if the roadside units are damaged by disasters or power outages, these functions cannot be provided. Therefore, we consider ITS function assistance using unmanned aerial vehicles (UAVs), which can spread information without being affected by the availability of roads and traffic congestion. Simply flying UAVs without a plan will cause problems such as delays due to unnecessary movement and information transmission to areas where vehicles do not exist. Therefore, we propose a method for predicting information diffusion by vehicle-to-vehicle communication to control the flight trajectory of UAVs, with the aim of quickly spreading information to many vehicles. To predict information diffusion, we use a reaction-diffusion model, which is a partial differential equation, and construct a model that considers the effects of vehicle-to-vehicle communication. The effectiveness of the proposed method is evaluated through the simulation, and the results show that the method performs better than the comparison methods.

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