Journal
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume 23, Issue 7, Pages 9736-9746Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2021.3107011
Keywords
Blockchain; intelligent transport system; LightGBM; Ethereum; big data
Categories
Funding
- National Key Research and Development Program of China [2018YFB1003205]
- National Natural Science Foundation of China [2018YFB1003205, 61902203]
- Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) Fund
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET) Fund, China
- Key Research and Development Plan-Major Scientific and Technological Innovation Projects of Shan Dong Province [2019JZZY020101]
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The study focuses on utilizing blockchain technology to address security issues in Intelligent Autonomous Transport Systems and enhance intelligent development in logistics transportation. By employing Ethereum as the underlying blockchain, sensitive information is securely recorded to ensure data integrity, while the LightGBM algorithm is used for vehicle and cargo matching. Results show high security prediction accuracy and superior performance of the proposed algorithm compared to others, demonstrating the potential for blockchain-based IATS in intelligent logistics transportation development.
The purposes are to investigate how blockchain can solve the security problems in Intelligent Autonomous Transport System (IATS) and intelligentize the logistics transportation development. Regarding the scarcity of trust and concentration of rights caused by the centralized structure of traditional logistics information systems, a blockchain-based IATS is proposed. The system employs Ethereum as the underlying blockchain to record sensitive information, such as system orders, cargos, and personnel information on the blockchain, ensuring the non-tampering and credibility of data. Simultaneously, an order management module, a warehouse management module, a transportation management module, a transaction management module, and a system management module are established. In the meantime, the Light Gradient Boosting Machine (LightGBM) algorithm is utilized to recommend vehicle and cargo matching during transportation. Finally, the constructed algorithm model is simulated to analyze its performance. Results demonstrate that the security prediction accuracy of the proposed algorithm reaches 88.72%; moreover, the security prediction precision, recall, and F1 of the proposed algorithm are considerably better than those of other algorithms. Furthermore, the actual effect of each algorithm is analyzed. The LightGBM algorithm outperforms other algorithms and unused algorithms in click rate, conversion rate, turnover rate, and average response time. Therefore, the constructed blockchain-based IATS has excellent security performance and prediction accuracy, which provides an experimental basis for the later intelligent logistics transportation development.
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