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Exploring the Impact of Interpretable Information Types on Driver's Situational Awareness and Performance During Driving Take-Over

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Cross-Cultural Design (HCII 2024)

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Abstract

In Level 3 (L3) autonomous driving, the system issues a take-over request to the driver if the Automated Driving System (ADS) fails or operates outside its design domain. The driver must takeover control and resume vehicle operation. This study demonstrates that in Level 3 (L3) autonomous vehicles, varied information presentation strategies—namely no explanation, reason explanation (Why), outcome explanation (What), and both reason and outcome explanation (What + Why)—significantly affect drivers’ situational awareness and take-over performance. The “What + Why” strategy yields the most significant improvements. Furthermore, the research highlights differences in the effectiveness of these strategies among less experienced drivers and a gender disparity in responses to the “Why” explanation, with males showing more favorable outcomes. In conclusion, effective information presentation is crucial in autonomous vehicle human-machine interfaces, particularly for L3 systems. This underscores the need for user-centered, interpretable AI that customizes information delivery according to driver-specific characteristics, optimizing performance and safety.

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Acknowledgments

This study was supported by the Natural Science Foundation of Hunan Province of China (No. 2023JJ30149).

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Correspondence to Xi Fu .

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Fu, X., Zou, Y., Tan, H. (2024). Exploring the Impact of Interpretable Information Types on Driver's Situational Awareness and Performance During Driving Take-Over. In: Rau, PL.P. (eds) Cross-Cultural Design. HCII 2024. Lecture Notes in Computer Science, vol 14702. Springer, Cham. https://doi.org/10.1007/978-3-031-60913-8_8

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  • DOI: https://doi.org/10.1007/978-3-031-60913-8_8

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