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Predicting drivers' takeover time for safe and comfortable vehicle control transitions: The role of spare capacity and driver characteristics.

作者信息

Liang Kexin, Calvert Simeon C, Nordhoff Sina, Li Ming, van Lint J W C

机构信息

Transport and Planning Department, Faculty of Civil Engineering and Geosciences, Delft University of Technology, The Netherlands.

Transport and Planning Department, Faculty of Civil Engineering and Geosciences, Delft University of Technology, The Netherlands.

出版信息

Appl Ergon. 2025 Nov;129:104603. doi: 10.1016/j.apergo.2025.104603. Epub 2025 Jul 31.

Abstract

Conditionally automated driving requires drivers to resume vehicle control within constrained time budgets upon receiving takeover requests. Accurately predicting drivers' takeover time (ToT) is essential for dynamically adjusting time budgets to individual needs across scenarios. This study addresses enduring challenges in reliability and interpretability of ToT prediction models by optimizing predictor selection. Using a driving simulator experiment, we examine the relationship between ToT, driver characteristics, and perceived Spare Capacity (pSC, a cognitive construct from Task-Capability Interface theory) using Category Boosting models. Results show that (i) incorporating 13 additional driver characteristics does not significantly improve prediction accuracy when pSC is already considered; and (ii) individual characteristics influence how drivers cognitively process takeover scenarios, and their predictive contribution likely overlaps with pSC. These findings suggest that monitoring cognitive states may be more effective for ToT prediction than extensive profiling of driver characteristics. This study provides a critical first step toward predictive frameworks for adaptive takeover strategies and offers guidance for designing personalized human-vehicle interactions.

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