Abstract
Reliability assessment methods are widely used in the reliability evaluation of transportation networks and transportation special equipment. The reliability assessment of Autonomous Transportation System (ATS) architecture can identify possible hidden problems and structural deficiencies before the implementation of ATS. The physical architecture of ATS maps the functional and logical architectures to the real world, hence, reliability assessment of the ATS architecture requires synthesizing information from all the three architectures. However, the current reliability assessment method of ATS architecture only took into account of the logical architecture of ATS. To meet this gap, a Markov chain model of the physical objects of ATS architecture is established, portraying the dynamic evolution of the physical object states, and failure rate and occupancy rate of physical objects is used to describe the reliability of the physical objects of ATS architecture, and the reliability of the physical objects and the importance of the physical objects in the ATS architecture is taken as the reliability index of ATS architecture. The method is applied to the reliability evaluation of the Vehicle Environment Awareness Service (VEAS) architecture, and the results show that the key physical objects that affect the reliability of the ATS architecture can be found by comparing the physical object importance and occupancy rate, and the reliability of the physical objects can be improved by raising the repairable rate and reducing the failure rate, thereby the reliability of the ATS architecture is promoted.
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This study was sponsored by the National Key R&D Program of China (2020YFB1600400).
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Shen, B., Liu, G., Cheng, S., Li, X., Li, K., Liang, C. (2023). Reliability Evaluation of Autonomous Transportation System Architecture Based on Markov Chain. In: Guiochet, J., Tonetta, S., Schoitsch, E., Roy, M., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops. SAFECOMP 2023. Lecture Notes in Computer Science, vol 14182. Springer, Cham. https://doi.org/10.1007/978-3-031-40953-0_17
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