Trustworthy Human-Machine Teaming in Autonomous Vehicles - A Computational Intelligence Approach: Develops computational intelligence-based methods to ensure trustworthy human-machine teaming in Avs

Authors

  • Dr. Yu Han Associate Professor of Computer Science, Shanghai Jiao Tong University, China Author

Keywords:

Trustworthy, Adoption, Simulation

Abstract

The advent of autonomous vehicles (AVs) promises transformative changes in transportation efficiency and safety. However, the integration of humans into the AV control loop introduces complexities related to trust, reliability, and safety. This paper proposes a computational intelligence approach to develop methods ensuring trustworthy human-machine teaming in AVs. We discuss the challenges, present a framework leveraging computational intelligence techniques, and demonstrate its effectiveness through simulations. The proposed approach enhances trust and reliability in AV operations, paving the way for widespread adoption.

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Published

03-02-2023

How to Cite

[1]
Dr. Yu Han, “Trustworthy Human-Machine Teaming in Autonomous Vehicles - A Computational Intelligence Approach: Develops computational intelligence-based methods to ensure trustworthy human-machine teaming in Avs”, J. of Artificial Int. Research and App., vol. 3, no. 1, pp. 1–12, Feb. 2023, Accessed: Nov. 22, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/69

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