Freeway merging area data sharing strategy based on blockchain technology
With the rapid development of Telematics technology, vehicle lane changing at motorway merging zone intersections has taken on new characteristics. For the different merging zone optimization frameworks in the study, there are differences in the sources of vehicle travel data and the departments involved in data interaction. To ensure the effectiveness and safety of merging zone optimization, differentiated data-sharing strategies need to be designed according to the characteristics and needs of different merging zone regions. Aiming at the efficient data interaction needs of highway road merging nodes in the Telematics environment, this study innovatively proposes a collaborative management mechanism with a hierarchical distributed ledger architecture. Relying on the distributed trust construction capability of blockchain technology, this scheme effectively solves the problem of trustworthy data storage and real-time sharing under a highly dynamic heterogeneous network environment by designing a dual-chain collaborative architecture with a differentiated consensus mechanism. In addition, this study constructs a cross-departmental data-sharing process based on the federated blockchain, which achieves a secure and efficient sharing mechanism for cross-departmental data in the highway field by taking each department as a node member of the federated chain. The double-layer blockchain architecture and cross-departmental data-sharing mechanism in this study provide new ideas and methods for solving the security problem of sharing data in the vehicle network in the highway merging area.
Authors
- X. Liu (ORCID: https://orcid.org/0000-0001-5700-4983)
- Jiacheng Fang (ORCID: https://orcid.org/0000-0002-7038-9897)
- Xiaoning Zhang (ORCID: https://orcid.org/0000-0002-5914-5437)
- Haiyang Wang (ORCID: https://orcid.org/0000-0002-1302-5747)
- Jialin He
- Huizhen Li (ORCID: https://orcid.org/0000-0002-1773-6749)
- Suming Shi (ORCID: https://orcid.org/0000-0002-4865-3137)
- Hui Jiang
Institutions
- Tongji University (CN)
- Heilongjiang University of Technology (CN)
- China Railway Group (China) (CN)
Publication Details
- Published
- 2025-07-24
- DOI
- https://doi.org/10.1117/12.3068581
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00