A probabilistic model of taking-over control from semi-autonomous vehicles
Kaindl, Hermann, and Paul, Gunther (2021) A probabilistic model of taking-over control from semi-autonomous vehicles. In: Advances in Intelligent Systems and Computing (1269) pp. 332-337. From: IHSED2020: 3rd International Conference on Human Systems Engineering and Design: future trends and applications, 22-24 September 2020, Pula, Croatia.
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Abstract
In automated driving scenarios with semi-autonomous vehicles of today and the near future, a request for taking-over control may at any time be communicated to a human driver. Empirical studies exist of, e.g., the effects of different modalities used in this human-machine interaction, and of drowsiness of drivers involved, depending on manual or automated driving. However, there is no model available yet of how the decision-making time in the course of taking-over control from the automated vehicle depends on the driver's drowsiness. Hence, we present a probabilistic model of the decision-making time as influenced by certain properties characterizing the driver’s drowsiness according to previous work.
| Item ID: | 65719 |
|---|---|
| Item Type: | Conference Item (Research - E1) |
| ISBN: | 978-3-030-58282-1 |
| Keywords: | Human Factors and Ergonomics (HFE), Probabilistic models, Automated Driving, Human-System Integration (HSI) |
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| Copyright Information: | © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 |
| Additional Information: | Proceedings of the 3rd International Conference on Human Systems Engineering and Design |
| Date Deposited: | 04 Feb 2021 02:25 |
| FoR Codes: | 40 ENGINEERING > 4002 Automotive engineering > 400204 Automotive safety engineering @ 50% 40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400702 Automation engineering @ 50% |
| SEO Codes: | 92 HEALTH > 9205 Specific Population Health (excl. Indigenous Health) > 920504 Occupational Health @ 50% 88 TRANSPORT > 8801 Ground Transport > 880109 Road Safety @ 50% |
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