天气与自行车运动的关系

Christopher Kane, Stefanos Kythreotis
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摘要

随着自行车作为一种有益的城市交通方式获得越来越多的牵引力和关注,世界不同地区出现了影响其采用和推广的不同因素。其中一个最广泛和最常见的因素是该地区的天气或气候,以及它如何促进或(更常见的是)阻碍骑自行车出行。虽然 "糟糕 "的天气似乎会对一个地区的自行车运动量产生负面影响,但这种直觉的可靠性受到了一些地区的挑战,例如,在 "糟糕 "的冬季条件下骑自行车是常态而非例外,或者骑自行车的人对阴雨天气相对漠不关心。因此,本文献综述旨在确定天气对不同地点骑车行为的实际影响,并揭示次要协变量与对天气的反应之间的关系。降雨、温度和风被认为是影响骑车行为的三个最重要的可测量天气参数。在大多数地方,开始下雨时骑车率会明显下降,温度阈值因地而异,而风的影响只有在蒲氏 5 度以上时才显著。一些研究还揭示了与可测量的天气参数相互作用的因素,这些因素对骑车行为的影响很大,而且看似很复杂。这些因素包括旅行目的、旅行者的社会人口、建筑环境特征以及对正常性的看法。确定这些协变量并讨论它们之间的相互关系,有助于解释为什么天气在某些地方对骑车者的影响似乎比在其他地方更大,同时也突出了未来研究的方向。
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Relationships Between Weather and Cycling
As cycling gains more traction and attention as a beneficial mode of urban transportation, different factors have emerged in different regions of the world to influence its adoption and promotion. One of the most wide-spread and colloquial of these factors is that of the weather or climate of the region, and how it may facilitate or, more often, dissuade cycling practices. Although it may appear intuitive that “poor” weather shall negatively impact the amount of cycling that occurs in a region, the reliability of this intuition is challenged by example locations where cycling in “poor” winter conditions is the norm rather than the exception, or where cyclists are relatively indifferent towards rainy weather. As such, the aim of this literature review is to identify the real effects of weather on cycling behaviour in different locations and uncover relationships between secondary covariates and responses to weather. Rainfall, temperature, and wind are identified as the three most important measurable weather parameters that affect cycling behaviour. In most locations, cycling rates drop significantly when it starts to rain, temperature thresholds vary between locations, and the effect of wind is only significant when above 5 Beaufort. Several studies also reveal factors that interact with measurable weather parameters to influence behaviour in significant and seemingly complex ways. These include the trip purpose, traveller sociodemographic, the characteristics of the built environment, and perceptions of normality. The identification of these covariates and a discussion about interrelations amongst them contributes to an explanation of why weather seems to affect cyclists in some places more than in others, while also highlighting directions for future research.
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