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Black Swan Theory for Navigating Trust in Mixed-Traffic Environments

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00141561" target="_blank" >RIV/00216224:14330/25:00141561 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/978-3-031-92474-3_6" target="_blank" >https://doi.org/10.1007/978-3-031-92474-3_6</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-92474-3_6" target="_blank" >10.1007/978-3-031-92474-3_6</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Black Swan Theory for Navigating Trust in Mixed-Traffic Environments

  • Original language description

    Connected and autonomous vehicles (CAVs) have revolutionized traffic systems, introducing mixed-driving environments where human-driving and driverless vehicles can coexist on the same roadways. This dynamic interaction has resulted in complex social driving behaviors, emphasizing the need for social trust management to balance interactions in mixed-driving environments effectively. This work presents our vision of a trust management framework designed for mixed driving environments. By gaining from the black swan theory, we address critical blind spots and vulnerabilities in current trust models. We offer insights into how trust relationships can be optimized in the face of uncertainty. Our approach aims to support reliable social networks and facilitate harmonious collaboration between human-driving and driverless vehicles, which promotes the safety and efficiency of mixed-traffic ecosystems.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    The 19th International Conference on Research Challenges in Information Science (RCIS)

  • ISBN

    9783031924736

  • ISSN

    1865-1348

  • e-ISSN

  • Number of pages

    16

  • Pages from-to

    87-102

  • Publisher name

    Springer

  • Place of publication

    Seville, Spain

  • Event location

    Seville, Spain

  • Event date

    Jan 1, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001545064600006