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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/149874


    Title: Collaborative Vehicle Collision Warning Based on Consensus Protocol
    Authors: 張宏慶
    Contributors: 資訊系
    Keywords: Consensus Protocol;Broadcast Storm;Vulnerable Road User;Collision Potential Zone;Collision Warning
    Date: 2023-11
    Issue Date: 2024-02-16 15:36:32 (UTC+8)
    Abstract: In recent years, the advent of innovative advanced driver-assistance systems (ADAS) and vehicle-to-everything (V2X) technology has heralded the beginning of a new era in driving. Many countries, including China, India, the United States, Italy, the Netherlands, Brazil, Vietnam, Taiwan, etc., all encompass a transportation system involving cars, motorcycles, and bicycles in their urban environments. However, these innovative technologies have not been fully implemented for two-wheeled transportation like motorcycles and bicycles, nor necessarily providing sufficient safety from a pedestrian’s perspective. In densely populated metropolitan areas, traffic complexity on provincial and county roads, combined with the widespread use of motorcycles and unique road usage habits, has made street safety a pressing concern. This research aims to enhance the early warning capability of vehicles equipped with various assistive systems and provide a proactive collision warning mechanism for vulnerable road users. We aim to modify the Stellar consensus protocol framework for higher safety, sharing spatial information detected by vehicle sensors so all road users can reach a consensus. Furthermore, we leverage the edge computing capabilities of vehicles and smart mobile devices to detect potential collision situations, addressing the issue of vulnerable road users lacking advanced driver-assistance systems. To verify the effectiveness of this mechanism, we used MATLAB and Simulink for numerical simulations to ensure the proposed mechanism accurately reflects complex traffic scenarios. The results demonstrate that our method effectively reduces positioning errors, meeting lane-level positioning requirements.
    Relation: 2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, 西安交通-利物浦大學（XJTLU）, pp.361-370
    Data Type: conference
    DOI link: https://doi.org/10.1109/CyberC58899.2023.00063
    DOI: 10.1109/CyberC58899.2023.00063
    Appears in Collections:[Department of Computer Science ] Proceedings

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