Supplementary data for the paper 'What driving style makes pedestrians think a passing vehicle is driving automatically?'

An important question in the development of automated vehicles (AVs) is which driving style AVs should adopt and how other road users perceive them. The current study aimed to determine which AV behaviours contribute to pedestrians’ judgements as to whether the vehicle is driving manually or automatically as well as judgements of likeability. We tested five target trajectories of an AV in curves: playback manual driving, two stereotypical automated driving conditions (road centre tendency, lane centre tendency), and two stereotypical manual driving conditions, which slowed down for curves and cut curves. In addition, four braking patterns for approaching a zebra crossing were tested: manual braking, stereotypical automated driving (fixed deceleration), and two variations of stereotypical manual driving (sudden stop, crawling forward). The AV was observed by 24 participants standing on the curb of the road in groups. After each passing of the AV, participants rated whether the car was driven manually or automatically, and the degree to which they liked the AV’s behaviour. Results showed that the playback manual trajectory was considered more manual than the other trajectory conditions. The stereotype automated ‘road centre tendency’ and ‘lane centre tendency’ trajectories received similar likeability ratings as the playback manual driving. An analysis of written comments showed that curve cutting was a reason to believe the car is driving automatically, whereas driving at a constant speed or in the centre was associated with automated driving. The sudden stop was the least likeable way to decelerate, but there was no consensus on whether this behaviour was manual or automated. It is concluded that AVs do not have to drive like a human in order to be liked.

自动驾驶汽车（Automated Vehicles, AVs）发展中的一项核心议题，在于其应当采用何种驾驶风格，以及其他道路使用者会如何感知该风格。本研究旨在探究自动驾驶汽车的哪些行为，会影响行人对车辆是人工驾驶还是自动驾驶的判断，以及行人对该车辆行为的好感度评价。我们针对弯道场景下的自动驾驶汽车，测试了五类目标行驶轨迹：回放人工驾驶轨迹、两类典型自动驾驶工况（倾向于行驶在道路中央、倾向于行驶在车道中央），以及两类典型人工驾驶工况（减速过弯与切弯）。此外，我们还测试了自动驾驶汽车接近人行横道（zebra crossing）时的四种制动模式：人工制动、典型自动驾驶制动（固定减速度），以及两类典型人工驾驶制动模式（急停与缓行）。共有24名分组站立在道路路缘处的参与者参与了本次观测实验。每辆自动驾驶汽车驶过之后，参与者需要对车辆是人工驾驶还是自动驾驶进行判断，并对该车辆的行为给出好感度评分。实验结果显示，回放的人工驾驶轨迹相较于其他轨迹工况，被更多参与者判定为人工驾驶。典型自动驾驶的“道路中央行驶倾向”与“车道中央行驶倾向”轨迹，其好感度评分与回放的人工驾驶轨迹相当。对参与者书面反馈的分析表明，切弯行为会让参与者认为车辆处于自动驾驶状态，而匀速行驶或保持在道路中央行驶则与自动驾驶相关。急停制动是最不受欢迎的减速方式，但参与者并未就该行为属于人工驾驶还是自动驾驶达成统一共识。研究表明，自动驾驶汽车无需以人类驾驶风格行驶，即可获得行人的好感。