Research and Application of an Automatic Test Sequence Generation Method Based on a Virtual Track Coordinate System
With the rapid development of China's railway system, track scenarios are becoming increasingly complex, characterized by a wide variety of engineering data tables and strong data coupling among them. The manual creation of test sequences is labor-intensive and computationally demanding, making the automatic generation of test sequences a topic of significant research interest. This paper proposes an automatic test sequence generation method based on a virtual track coordinate system. The method includes the construction of the virtual track coordinate system, which is based on track direction, chainage interruption information, and mileage system transformation relationships, as well as a mapping method between the kilometer marker system and configuration attribute sets within the virtual track coordinate system. The method is validated using real-world engineering data under complex track scenarios, focusing on track conditions and RBC handovers. The results demonstrate that the proposed method can automatically generate test sequences and verify their correctness. Compared to manual test sequence creation and other automatic generation methods, the virtual track coordinate system-based approach is better suited to complex track scenarios and the coupling of diverse test sequences. Furthermore, the method of establishing the virtual track coordinate system can be applied to other coordinate system modeling needs involving complex mileage systems and chainage interruptions, offering high reusability. Therefore, this method enhances the automation level of data testing in train control systems.
Authors
- Bailiang Wang (ORCID: https://orcid.org/0009-0009-6136-6675)
Institutions
- Southwest Jiaotong University (CN)
Publication Details
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1109/eit63098.2024.10762231
- Primary Topic
- Educational Technology and Assessment
- Type
- article
- Field-Weighted Citation Impact
- 0.00