Digital Twin-based Collision and Conflict Warning System for Internet of Vehicles

As an important part of the future intelligent transportation, the Internet of Vehicles is one of the indispensable technology to realize intelligent transportation. With the development of the technology of the Internet of Vehicles, Safety issues are becoming increasingly prominent. If it's po...

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Bibliographic Details
Published in2024 4th International Conference on Neural Networks, Information and Communication (NNICE) pp. 99 - 104
Main Author Wang, Yuxuan
Format Conference Proceeding
LanguageEnglish
Published IEEE 19.01.2024
Subjects
Alarm systems
collision warning
dangerous areas
data classification
digital twin
Digital twins
driving habits
Filters
Internet
Internet of vehicles
Pedestrians
Prediction algorithms
Safety
travel habits
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Summary:As an important part of the future intelligent transportation, the Internet of Vehicles is one of the indispensable technology to realize intelligent transportation. With the development of the technology of the Internet of Vehicles, Safety issues are becoming increasingly prominent. If it's possible to receive an early warning and make decisions for vehicles before dangers arise, the likelihood of accidents can be significantly reduced. This article aims to design a vehicle network collision conflict warning system based on digital twins. Utilizing the features of digital twins, it broadly collects and analyzes drivers' historical travel habits and driving behaviors. The system anticipates which vehicles will appear in different sections at different times and predicts their next potential actions. It then categorizes and filters out dangerous drivers and determines the danger zones. Subsequently, the danger zones and subsequent system decision recommendations are broadcast to pedestrians and vehicles within the vicinity. This article uses MATLAB for simulation, employs the k-means algorithm for categorization, and calculates and plots the warning zones. Ultimately, the results fully met expectations.
DOI:10.1109/NNICE61279.2024.10498861