Modelling cycling to school in Finland

Emilia Suomalainen , Henna Malinen , Marko Tainio
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Abstract

Active travel to school is an important contributor to the physical activity levels of children and adolescents and the source of many health benefits. In this work, we model cycling to school in Finland. The probability to cycle on a given trip is modelled using a binary logistic regression model based on trip length, average route gradient, the cyclist’s gender, and age. Variables denoting the city regions were also included to account for differences in cycling cultures and infrastructure. In addition, weather variables were added as cycling levels in Finland are highly dependent on the season. Air temperature and the presence of snow were found to reflect well the observed seasonal variations. The observed influence of winter conditions on trip distances and the cycling of girls is also replicated in the model through interaction terms. This model is employed to explore two sustainable mobility scenarios: a scenario where the cycling of girls increases to the same level as that of boys and a scenario where all school children cycle as much as those living in Oulu, Finland’s top cycling region. Our results suggest that it would be possible to increase the number of trips by bicycle and cycled mileage significantly, up to 76 % in the Oulu scenario, even though school children already cycle much more than the general population.

芬兰骑自行车上学的模式
积极的上学方式是提高儿童和青少年体育锻炼水平的重要因素,也是许多健康益处的来源。在这项工作中,我们模拟了芬兰骑自行车上学的情况。根据行程长度、平均路线坡度、骑车人的性别和年龄,使用二元逻辑回归模型对特定行程中骑车的概率进行建模。此外,还加入了表示城市地区的变量,以考虑骑车文化和基础设施的差异。此外,还加入了天气变量,因为芬兰的自行车运动水平与季节有很大关系。研究发现,气温和是否下雪很好地反映了观察到的季节变化。模型中还通过交互项复制了观察到的冬季条件对出行距离和女孩骑车的影响。我们利用该模型探讨了两种可持续交通情景:一种情景是女孩骑自行车的比例与男孩持平,另一种情景是所有学童都像生活在芬兰骑自行车最多的地区奥卢的学童一样骑自行车。我们的研究结果表明,尽管学龄儿童骑自行车的比例已经远远高于普通人群,但骑自行车出行的次数和里程数仍有可能大幅增加,在奥卢方案中,骑自行车出行的比例最高可达 76%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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