The Propensity to Cycle Tool：一个可持续交通规划的开源在线系统
The Propensity to Cycle Tool: An open source online system for sustainable transport planning
摘要：
让人们骑自行车是世界各地交通规划机构越来越普遍的目标。越来越多的证据表明，高质量的基础设施可以提高当地的自行车使用率。然而，为了使基础设施和其他自行车措施有效，重要的是要在正确的地方进行干预，例如沿着潜在需求很高的“愿望线”。这就产生了对工具和方法的需求，以帮助回答“在哪里建造？'.在简要回顾了与此问题相关的政策和研究背景之后，本文介绍了这样一个工具的设计、特点和潜在应用。自行车倾向工具（PCT）是一个在线的互动规划支持系统，最初是为了探索和绘制英格兰各地的自行车潜力而开发的（见www.pct.bike）。基于出发地-目的地数据，它在区域、期望线路、路线和路线网络级别上对当前的自行车水平和基于里约热内卢的“自行车未来”进行建模和可视化。四个场景，包括“荷兰人”和“电动自行车”，探讨会发生什么，如果英国人骑自行车一样多，荷兰人和电动自行车对自行车吸收的潜在影响。投资的成本效益不仅取决于额外循环次数，还取决于更广泛的影响，如健康和碳效益。PCT在区域、期望线和路线级别报告每个场景的这些情况。PCT是开源的，便于创建额外的场景并在新的环境中部署。我们的结论是，PCT说明了在线工具的潜力，为交通决策提供信息，并提出了更广泛的问题，模型应如何在交通规划中使用。
英文摘要：
Getting people cycling is an increasingly common objective in transport planning institutions worldwide. A growing evidence base indicates that high quality infrastructure can boost local cycling rates. Yet for infrastructure and other cycling measures to be effective, it is important to intervene in the right places, such as along 'desire lines' of high latent demand. This creates the need for tools and methods to help answer the question 'where to build?'. Following a brief review of the policy and research context related to this question, this paper describes the design, features and potential applications of such a tool. The Propensity to Cycle Tool (PCT) is an online, interactive planning support system which was initially developed to explore and map cycling potential across England (see www.pct.bike). Based on origin-destination data, it models and visualises cycling levels at area, desire line, route and route network levels, for current levels of cycling, and for scenario-based 'cycling futures'. Four scenarios are presented, including 'Go Dutch' and 'Ebikes', which explore what would happen if English people cycled as much as Dutch people and the potential impact of electric cycles on cycling uptake. The cost effectiveness of investment depends not only on the number of additional trips cycled, but on wider impacts such as health and carbon benefits. The PCT reports these at area, desire line, and route level for each scenario. The PCT is open source, facilitating the creation of additional scenarios and its deployment in new contexts. We conclude that the PCT illustrates the potential of online tools to inform transport decisions and raises the wider issue of how models should be used in transport planning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
