Data underlying the publication: Modelling perceived risk and trust in driving automation reacting to merging and braking vehicles

This dataset is derived from a driving simulator study that explored the dynamics of perceived risk and trust in the context of driving automation. The study involved 25 participants who were tasked with monitoring SAE Level 2 driving automation features (Adaptive Cruise Control and Lane Centering) while encountering various driving scenarios on a motorway. These scenarios included merging and hard-braking events with different levels of criticality. This dataset contains kinetic data from the driving simulator, capturing variables such as vehicle position, velocity, and acceleration among others. Subjective ratings of perceived risk and trust, collected post-event for regression analysis are also included.

本数据集源自一项驾驶模拟器研究，该研究旨在探究驾驶自动化场景下感知风险与信任的动态演化规律。该研究招募25名受试者，要求其在高速公路上遭遇各类驾驶场景时，监控SAE二级（SAE Level 2）驾驶自动化功能——自适应巡航控制（Adaptive Cruise Control）与车道居中（Lane Centering）。此类场景涵盖不同临界等级的车道汇入与紧急制动事件。本数据集包含驾驶模拟器采集的动力学数据，涵盖车辆位置、速度、加速度等多项变量；此外还包含事件后采集的、用于回归分析的感知风险与信任主观评分。