School of Psychology, Department of Basic Psychology, University of Minho, Portugal.
Accid Anal Prev. 2013 Mar;51:11-7. doi: 10.1016/j.aap.2012.10.018. Epub 2012 Nov 27.
Road traffic sounds are a major source of noise pollution in urban areas. But recent developments such as low noise pavements and hybrid/electric engine vehicles cast an optimistic outlook over such an environmental problem. However, it can be argued that engine, tire, and road noise could be relevant sources of information to avoid road traffic conflicts and accidents. In this paper, we analyze the potential trade-offs of traffic-noise abatement approaches in an experimental study, focusing for the first time on the impact and interaction of relevant factors such as pavement type, vehicle type, listener's age, and background noise, on vehicle detection levels. Results reveal that vehicle and pavement type significantly affect vehicle detection. Age is a significant factor, as both younger and older people exhibit lower detection levels of incoming vehicles. Low noise pavements combined with all-electric and hybrid vehicles might pose a severe threat to the safety of vulnerable road users. All factors interact simultaneously, and vehicle detection is best predicted by the loudness signal-to-noise ratio.
道路交通噪声是城市噪声污染的主要来源。但近年来,低噪声路面和混合动力/电动汽车等发展趋势对这一环境问题带来了乐观的前景。然而,也有人认为,发动机、轮胎和道路噪声可能是避免道路交通冲突和事故的相关信息来源。在本文中,我们通过实验研究分析了交通噪声缓解方法的潜在权衡,首次重点关注路面类型、车辆类型、听众年龄和背景噪声等相关因素对车辆检测水平的影响和相互作用。结果表明,车辆和路面类型对车辆检测有显著影响。年龄是一个重要因素,因为年轻人和老年人对过往车辆的检测水平都较低。低噪声路面与全电动汽车和混合动力汽车相结合,可能对弱势道路使用者的安全构成严重威胁。所有因素同时相互作用,车辆检测最好由响度信噪比来预测。