Implicit communication in cyclist-vehicle interaction: Examining the influence of driving dynamics in interactions with turning (automated) vehicles on cyclists' perceived safety, behavioral intention, and risk anticipation

A. Marie Harkin , Aline Mangold , Kevin A. Harkin , Tibor Petzoldt
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Abstract

Successful and safe management of interactions between cyclists and motorized vehicles often includes implicit communication, such as vehicle motion signals. While the introduction of automated vehicles (AVs) is anticipated to increase safety for cyclists by eliminating human error, it is still unclear how they should communicate implicitly in complex traffic scenarios. The turning maneuver constitutes a complex and ambiguous scenario, as it involves vehicle deceleration even when there is no intention to halt for the cyclist, proceeding straight ahead. A video-based laboratory study incorporating a bicycle setup examined the influence of four driving dynamics and automation status on cyclists' risk anticipation, perceived safety, and intention to continue to cycle through an intersection. Forty-two participants viewed videos of an oncoming vehicle making a left turn at an intersection from the perspective of a cyclist traveling straight through the intersection. The results indicated that participants perceived early and continuous braking of the vehicle ("passive yield") as the most favorable approach (reduced risk anticipation, higher perceived safety, and greater intention to continue to cycle through the intersection), even when compared to later but stronger braking ("active yield"). The objectively riskiest maneuver that would result in a collision ("collision") was evaluated as the least desirable. A rule-violating yet objectively safe maneuver (accelerating to exit the conflict area before the cyclist; "no yield") led to increased risk anticipation but not to lower perceived safety or reduced intention to continue to cycle through the intersection compared to active yield. The displayed automation status had minimal influence overall, although participants in the passive yield condition expressed greater uncertainty regarding their intention to continue to cycle through the intersection in interactions with AVs compared to MVs. It appears that natural driving dynamics exhibited by "good" human drivers could represent a promising approach to ensuring the safety and comfort of cyclists in interactions with AVs. Here, early and continuous braking is preferable to later and stronger braking.

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骑车人与车辆互动中的隐性交流:研究在与转弯(自动驾驶)车辆的互动中,驾驶动态对骑车人的安全感、行为意向和风险预期的影响
成功、安全地管理骑车人与机动车之间的互动通常包括隐性交流,如车辆运动信号。虽然自动驾驶汽车(AV)的引入有望通过消除人为错误来提高骑车人的安全,但目前仍不清楚自动驾驶汽车在复杂的交通场景中应如何进行隐式交流。转弯动作是一个复杂而模糊的场景,因为它涉及到车辆减速,即使没有为骑车人停车的意图,而是径直向前行驶。一项基于视频的实验室研究结合了自行车设置,考察了四种驾驶动态和自动化状态对骑车人的风险预期、安全感和继续骑车通过交叉路口的意愿的影响。42 名参与者从直行通过交叉路口的骑车人的角度观看了迎面而来的车辆在交叉路口左转的视频。结果表明,即使与较晚但较强的制动("主动让行")相比,参与者也认为车辆较早且持续的制动("被动让行")是最有利的方法(风险预期降低、安全感提高、继续骑车通过交叉路口的意愿增强)。客观上会导致碰撞("碰撞")的风险最大的操作被认为是最不可取的。与主动让行相比,违反规则但客观上安全的操作(加速,在骑车人之前驶出冲突区;"不让行")会导致风险预期增加,但不会降低安全感,也不会降低继续骑车通过交叉路口的意愿。虽然被动让行条件下的参与者在与自动驾驶汽车互动时,对自己是否打算继续骑自行车通过交叉路口的不确定性高于自动驾驶汽车,但显示的自动驾驶状态对整体影响很小。由此看来,"优秀 "的人类驾驶员所表现出的自然驾驶动态可能是确保骑自行车者在与自动驾驶汽车互动时的安全性和舒适性的一种有前途的方法。在这种情况下,早期持续制动比晚期加强制动更可取。
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