Work-in-Progress: Traded Control Transfer for Managing Real-Time Sensor Uncertainties in Autonomous Vehicle
<|reference_start|>Work-in-Progress: Traded Control Transfer for Managing Real-Time Sensor Uncertainties in Autonomous Vehicle: At Levels 2 and 3 of autonomous driving defined by the Society of Auto-motive Engineers, drivers must take on certain driving responsibilities, and automated driving must sometimes yield to human control. This situation can occur in real time due to uncertainties in sensor measurements caused by environmental factors like fog or smoke. To address this challenge, we propose a method to manage real-time sensor uncertainties in autonomous vehicles by monitoring sensor conflicts and dynamically adjusting control authority to maintain safe operation. However, to achieve this, we have introduced a novel metric called the Degree of Conflicts (DoC), which quantifies the conflict between real-time sensor data by measuring the differences between data from multiple sensors. Our approach aims to demonstrate the importance of selecting an appropriate DoC threshold for transferring control between the automation agent and the human driver. The results have shown that choosing the correct DoC threshold can enhance safety by promptly handing over the driving control from the automation system to the human driver in challenging conditions.<|reference_end|>
@article{sourav2024work-in-progress:,
    title={Work-in-Progress: Traded Control Transfer for Managing Real-Time Sensor
  Uncertainties in Autonomous Vehicle},
    author={Md Sakib Galib Sourav (1), Liang Cheng (1) ((1) University of Toledo,
  Toledo, USA)},
    journal={arXiv preprint arXiv:2410.06345},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.06345},
    primaryClass={eess.SY cs.SY}
}