Construction of autonomous transportation system architecture based on system engineering methodology

Zhou, Zi-sheng; Cai, Ming; Xiong, Chen; Deng, Zhuolin; Yu, Yuezhao

doi:10.1109/itsc55140.2022.9921842

Cited by 7 publications

(1 citation statement)

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“…By ATS physical architecture, Deng et al [15] defne the physical architecture of ATS and form the theoretical basis. Zhou et al [16] build the physical architecture of ATS and create the groundwork for application. [20] collect information in aviation safety reports and successfully complete the mining latent topics task.…”

Section: Autonomous Transportation System (Ats)mentioning

confidence: 99%

Intergeneration Division Based on Key Component Analysis in an Autonomous Transportation System Using the Natural Language Processing Method

Gou

Xiong

2023

Journal of Advanced Transportation

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Advancement of emerging technologies and increasing of transport demands accelerate the evolution of the autonomous transportation system (ATS). Framework and architecture of ATS are becoming a research hotspot; however, by far, few studies on transportation intergeneration division are not basically involved. Previous works indicate that key components are critical representation in the distinguishing of long-term era. Besides, massive text material accumulates as the research work goes on, and natural language processing technique keeps developing, which makes quantitative research on key components in intergeneration division become possible. In this work, a method based on the massive text analysis is proposed. First, the LDA2vec is used to get the relationship between components and other elements. Then, a word set is from the component word set extraction module based on component items. Finally, the component word set is clustered to get ATS generation and to generate key components. Based on an analysis of large-scale important traffic texts, our method divides the traffic system into three generations for Chinese traffic from 2010 to 2022. The key components of our method given are consistent with human cognition of ATS. Successful application indicates that this work can be extended to other intergeneration division fields.

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Section: Autonomous Transportation System (Ats)mentioning

confidence: 99%