Tian Kai, Tzigieras Athanasios, Wei Chongfeng, Lee Yee Mun, Holmes Christopher, Leonetti Matteo, Merat Natasha, Romano Richard, Markkula Gustav
Institute for Transport Studies, University of Leeds, Leeds, LS1 9JT, UK.
Institute for Transport Studies, University of Leeds, Leeds, LS1 9JT, UK.
Accid Anal Prev. 2023 Sep;190:107173. doi: 10.1016/j.aap.2023.107173. Epub 2023 Jun 17.
Society greatly expects the widespread deployment of automated vehicles (AVs). However, the absence of a driver role results in unresolved communication issues between pedestrians and AVs. Research has shown the crucial role of implicit communication signals in this context. Nonetheless, it remains unclear how pedestrians subjectively estimate vehicle behaviour and whether they incorporate these estimations as part of their crossing decisions. For the first time, this study explores the impact of implicit communication signals on pedestrians' subjective estimations of approaching vehicle behaviour across a wide range of experimental traffic scenarios and on their crossing decisions in the same scenarios through a comprehensive analysis. Two simulator tasks, namely a natural road crossing task and a vehicle behaviour estimation task, were designed with controlled time to collision, vehicle speed, and deceleration behaviour. A novel finding is that the correlation between crossing decisions and vehicle behaviour estimations depends on the traffic scenario. Pedestrians' recognition of different deceleration behaviour aligned with their crossing decisions, supporting the notion that they actively estimate vehicle behaviour as part of their decision-making process. However, if the traffic gap was long enough, the effects of vehicle speed were the opposite between crossing decisions and estimations, suggesting that vehicle behaviour estimation may not directly impact crossing decisions when the time gap to the vehicle is large. We also found that pedestrians crossed the street earlier and estimated yielding behaviour more accurately in early-onset braking scenarios than in late-onset braking scenarios. Interestingly, vehicle speed significantly affected pedestrians' estimations, with pedestrians tending to perceive low vehicle speed as yielding behaviour regardless of whether the vehicle yielded. Finally, we demonstrated that visual cue τ̇ is a practical indicator for controlling the vehicle deceleration evidence in the experiment. In conclusion, these findings reveal in detail the role of deceleration parameters as implicit communication signals between pedestrians and AVs, with implications for road crossing safety and the development of AVs.
社会对自动驾驶车辆（AVs）的广泛应用寄予厚望。然而，由于缺少驾驶员这一角色，行人和自动驾驶车辆之间的沟通问题仍未得到解决。研究表明，在这种情况下，隐含沟通信号起着至关重要的作用。尽管如此，目前尚不清楚行人如何主观估计车辆行为，以及他们是否将这些估计纳入过马路决策的一部分。本研究首次通过全面分析，探讨了隐含沟通信号在广泛的实验交通场景中对行人对接近车辆行为的主观估计的影响，以及在相同场景中对行人过马路决策的影响。设计了两个模拟器任务，即自然过马路任务和车辆行为估计任务，并对碰撞时间、车速和减速行为进行了控制。一个新发现是，过马路决策和车辆行为估计之间的相关性取决于交通场景。行人对不同减速行为的认知与他们的过马路决策一致，这支持了他们在决策过程中积极估计车辆行为的观点。然而，如果交通间隙足够长，车速在过马路决策和估计之间的影响则相反，这表明当与车辆的时间间隙较大时，车辆行为估计可能不会直接影响过马路决策。我们还发现，与晚发性制动场景相比，行人在早发性制动场景中过马路更早，并且对让行行为的估计更准确。有趣的是，车速显著影响行人的估计，无论车辆是否让行，行人往往将低车速视为让行行为。最后，我们证明了视觉线索τ̇是实验中控制车辆减速证据的一个实用指标。总之，这些发现详细揭示了减速参数作为行人和自动驾驶车辆之间隐含沟通信号的作用，对过马路安全和自动驾驶车辆的发展具有启示意义。
