Supplementary data for the paper 'Once a driver, always a driver—Manual driving style persists in automated driving takeover'

As automated vehicles require human drivers to resume control in critical situations, predicting driver takeover behaviour could be beneficial for safe transitions of control. While previous research has explored predicting takeover behaviour in relation to driver state and traits, little work has examined the predictive value of manual driving style. We hypothesised that drivers’ behaviour during manual driving is predictive of their takeover behaviour when resuming control from an automated vehicle. We assessed 38 drivers with varying experience in a high-fidelity driving simulator. After completing manual driving sessions to assess their driving style, participants performed an automated driving task, typically on a subsequent date. Measures of driving style from manual driving sessions, including headway and lane change speed, were found to be predictive of takeover behaviour. The level of driving experience was associated with the behavioural measures, but correlations between measures of manual driving style and takeover behaviour remained after controlling for driver experience. Our findings demonstrate that how drivers reclaim control from their automated vehicle is not an isolated phenomenon but is associated with manual driving behaviour and driving experience. Strategies to improve takeover safety and comfort could be based on driving style measures, for example by the automated vehicle adapting its behaviour to match a driver’s driving style.

鉴于自动驾驶车辆（automated vehicles）在紧急场景下需要人类驾驶员接管控制权，预测驾驶员的接管行为（takeover behaviour）有助于实现安全的控制权切换。过往研究多围绕驾驶员状态与特质展开接管行为预测相关探索，但鲜有研究探讨手动驾驶风格的预测价值。本研究提出假设：驾驶员在手动驾驶阶段的行为可用于预测其从自动驾驶车辆接管控制权时的接管行为。我们在高保真驾驶模拟器中对38名驾驶经验各异的驾驶员开展了实验评估。参与者首先完成手动驾驶环节以评估其驾驶风格，后续通常在另一实验日开展自动驾驶任务。研究发现，手动驾驶环节中采集的驾驶风格指标（包括跟车时距与变道速度）可用于预测接管行为。驾驶经验水平与上述行为指标存在关联，但在控制驾驶员经验变量后，手动驾驶风格指标与接管行为之间的相关性依然显著。本研究结果表明，驾驶员从自动驾驶车辆处收回控制权的行为并非孤立现象，而是与手动驾驶行为及驾驶经验密切相关。可基于驾驶风格指标制定提升接管安全性与舒适性的策略，例如让自动驾驶车辆调整自身行为以匹配驾驶员的驾驶风格。