Driven by advancing technology and evolving demands, transportation systems are rapidly progressing toward higher levels of autonomy, giving rise to the Autonomous Transportation Systems (ATS) framework. Centering on autonomous perception, learning, decision-making, and response capabilities, the ATS framework outlines the vision of future transportation systems. However, as current systems remain at low autonomy levels, identifying key elements that can significantly drive further autonomy is critical. Therefore, this study examines an autonomous driving intersection-crossing scenario, analyzing ATS elements—components, demands, services, functions, and technologies—within this context to establish a specialized ATS sub-framework. Considering the relationships between function elements and function domains, we utilize analytic network process to identify essential functions. Based on these evaluations, we rank and analyze key functions. The results indicate that safety-related functions score relatively high, aligning with the public’s awareness of traffic safety and underscoring the critical role of safety assurance in advancing transportation development. Response-oriented functions are also favored, suggesting that decision-makers prioritize functions that have a direct impact on users. The proposed approach and findings provide valuable insights for ATS framework research and practical engineering applications.


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    Title :

    Identification of Key Functions in Autonomous Driving Intersection-Crossing Scenario Using the Autonomous Transportation System Framework


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Liu, Jun (editor) / Yang, Jianjian (editor) / Xu, Minyi (editor) / Yu, Quan (editor) / Shen, Wenchao (editor) / Huang, Xiangzhi (author) / Xiao, Yao (author) / Cai, Ming (author)

    Conference:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Publication date :

    2025-03-28


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English






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