Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Hörselgången 4, 41756 Göteborg, Sweden.
Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Hörselgången 4, 41756 Göteborg, Sweden; Veoneer Research, Veoneer Sweden AB, Wallentinsvägen 22, 44737 Vårgårda, Sweden.
Accid Anal Prev. 2020 Jul;142:105569. doi: 10.1016/j.aap.2020.105569. Epub 2020 May 20.
Overtaking cyclists is challenging for drivers because it requires a well-timed, safe interaction between the driver, the cyclist, and the oncoming traffic. Previous research has investigated this manoeuvre in different experimental environments, including naturalistic driving, naturalistic cycling, and simulator studies. These studies highlight the significance of oncoming traffic-but did not extensively examine the influence of the cyclist's position within the lane. In this study, we performed a test-track experiment to investigate how oncoming traffic and position of the cyclist within the lane influence overtaking. Participants overtook a robot cyclist, which was controlled to ride in two different lateral positions within the lane. At the same time, an oncoming robot vehicle was controlled to meet the participant's vehicle with either 6 or 9 s time-to-collision. The order of scenarios was randomised over participants. We analysed safety metrics for the four different overtaking phases, reflecting drivers' safety margins to rear-end, head-on, and side-swipe collisions, in order to investigate the two binary factors: 1) time gap between ego vehicle and oncoming vehicle, and 2) cyclist lateral position. Finally, the effects of these two factors on the safety metrics and the overtaking strategy (either flying or accelerative depending on whether the overtaking happened before or after the oncoming vehicle had passed) were analysed. The results showed that, both when the cyclist rode closer to the centre of the lane and when the time gap to the oncoming vehicle was shorter, safety margins for all potential collisions decreased. Under these conditions, drivers-particularly female drivers-preferred accelerative over flying manoeuvres. Bayesian statistics modelled these results to inform the development of active safety systems that can support drivers in safely overtaking cyclists.
超越自行车骑手对司机来说是一项挑战，因为这需要司机、自行车骑手和迎面而来的交通之间进行适时、安全的互动。先前的研究已经在不同的实验环境中研究了这种操作，包括自然驾驶、自然骑行和模拟器研究。这些研究强调了迎面而来的交通的重要性，但并没有广泛研究自行车骑手在车道内位置的影响。在这项研究中，我们进行了一个测试轨道实验，以研究迎面而来的交通和自行车骑手在车道内的位置如何影响超车。参与者超越了一个机器人自行车手，机器人自行车手被控制在车道内两个不同的横向位置骑行。与此同时，一辆迎面而来的机器人车辆被控制与参与者的车辆相遇，时间间隔为 6 秒或 9 秒。场景的顺序在参与者中随机排列。我们分析了四个不同超车阶段的安全指标，反映了驾驶员与追尾、正面碰撞和侧面碰撞的安全裕度，以研究两个二进制因素：1）自身车辆与迎面而来的车辆之间的时间间隔，以及 2）自行车骑手的横向位置。最后，分析了这两个因素对安全指标和超车策略（根据超车是在迎面而来的车辆通过之前还是之后发生，是飞行还是加速）的影响。结果表明，当自行车骑手靠近车道中心骑行且与迎面而来的车辆的时间间隔更短时，所有潜在碰撞的安全裕度都会降低。在这些条件下，司机——尤其是女司机——更喜欢加速而不是飞行操作。贝叶斯统计分析这些结果，以告知主动安全系统的开发，这些系统可以帮助司机安全地超越自行车骑手。
