Past studies show that women cycle at a lower rate than men due to various factors; few studies examine attitudes and perceptions of women cyclists on a large scale. This study aims to fill that gap by examining the cycling behaviors of women cyclists across multiple cities in North America. We analyzed an online survey of 1,868 women cyclists in the US and Canada, most of whom were confident when cycling. The survey recorded respondents’ cycling skills, attitude, perceptions of safety, surrounding environment, and other factors that may affect the decision to bicycle for transport and recreation. We utilized tree-based machine learning methods (e.g., bagging, random forests, boosting) to select the most common motivations and concerns of these cyclists. Then we used chi-squared and non-parametric tests to examine the differences among cyclists of different skills and those who cycled for utilitarian and non-utilitarian purposes. Tree-based model results indicated that concerns about the lack of bicycle facilities, cycling culture, cycling’s practicality, sustainability, and health were among the most important factors for women to cycle for transport or recreation. We found that very few cyclists cycled by necessity. Most cyclists, regardless of their comfort level, preferred cycling on facilities that were separated from vehicular traffic (e.g., separated bike lanes, trails). Our study suggests opportunities for designing healthy cities for women. Cities may enhance safety to increase cycling rates of women by tailoring policy prescriptions for cyclists of different skill groups who have different concerns. Strategies that were identified as beneficial across groups, such as investing in bicycle facilities and building a cycling culture in communities and at the workplace, could be useful to incorporate in long-range planning efforts.

中文翻译：

---

促进女性骑自行车：对北美骑自行车者的探索性研究

以往的研究表明，由于各种因素，女性的自行车运动速度要比男性低。很少有研究大规模调查女性骑自行车者的态度和看法。这项研究旨在通过研究北美多个城市的女子自行车骑手的行为来填补这一空白。我们分析了对美国和加拿大的1,868名女性骑自行车者的在线调查，其中大多数人对骑自行车充满信心。该调查记录了受访者的骑自行车技能，态度，安全感，周围环境以及其他可能影响骑自行车出行和娱乐的决定的因素。我们利用基于树的机器学习方法（例如，装袋，随机森林，助推）来选择这些自行车手最常见的动机和关注点。然后，我们使用卡方检验和非参数检验来检验具有不同技能的自行车手与出于功利和非功利目的骑自行车的人之间的差异。基于树的模型结果表明，对缺乏自行车设施，自行车文化，自行车的实用性，可持续性和健康的担忧是妇女骑自行车进行运输或娱乐的最重要因素。我们发现很少有骑自行车者根据需要骑自行车。大多数骑车者，无论舒适度如何，都喜欢在与车辆交通分开的设施（例如分开的自行车道，小径）骑自行车。我们的研究提出了为女性设计健康城市的机会。城市可以通过为关注不同技能的不同骑自行车者量身定制政策规定，从而提高安全性，从而提高女性的自行车骑行率。被确定为对整个群体有益的策略，例如投资自行车设施以及在社区和工作场所建立自行车文化，可能会有益于长期计划工作。