Abstract Mobile activity tracking data, i.e. data collected by mobile applications that enable activity tracking based on the use of the Global Navigation Satellite Systems (GNSS), contains information on cycling in urban areas at an unprecedented spatial and temporal extent and resolution. It can be a valuable source of information about the quality of bicycling in the city. Required is a notion of quality that is derivable from plain GNSS trajectories. In this article, we quantify urban cycling quality by estimating the fluency of cycling traffic using a large set of GNSS trajectories recorded with a mobile tracking application. Earlier studies have shown that cyclists prefer to travel continuously and without halting, i.e. fluently. Our method extracts trajectory properties that describe the stopping behaviour and dynamics of cyclists. It aggregates these properties to segments of a street network and combines them in a descriptive index. The suitability of the data to describe the cyclists' behaviour with street-level detail is evaluated by comparison with various data from independent sources. Our approach to characterizing cycling traffic fluency offers a novel view on the cyclability of a city that could be valuable for urban planners, application providers, and cyclists alike. We find clear indications for the data's ability to estimate characteristics of city cycling quality correctly, despite behaviour patterns of cyclists not caused by external circumstances and the data's inherent bias. The proposed quality measure is adaptable for different applications, e.g. as an infrastructure quality measure or as a routing criterion.

中文翻译：

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使用大型移动活动跟踪数据表征自行车交通的流畅性

摘要 移动活动跟踪数据，即基于全球导航卫星系统 (GNSS) 的使用启用活动跟踪的移动应用程序收集的数据，包含以前所未有的空间和时间范围和分辨率在城市地区骑自行车的信息。它可以成为有关城市自行车质量的宝贵信息来源。要求是可从普通 GNSS 轨迹推导出来的质量概念。在本文中，我们通过使用移动跟踪应用程序记录的大量 GNSS 轨迹估计自行车交通的流畅性来量化城市自行车质量。较早的研究表明，骑自行车的人更喜欢连续行驶而不停下来，即流畅地行驶。我们的方法提取描述骑自行车者的停止行为和动态的轨迹属性。它将这些属性聚合到街道网络的各个部分，并将它们组合在一个描述性索引中。通过与来自独立来源的各种数据进行比较，评估数据是否适用于描述具有街道级细节的骑自行车者的行为。我们表征自行车交通流畅性的方法为城市的可循环性提供了一种新颖的观点，这对城市规划者、应用程序提供商和骑自行车者都可能有价值。尽管骑自行车者的行为模式不是由外部环境和数据的固有偏差引起的，但我们发现数据能够正确估计城市自行车质量特征的能力有明确的迹象。建议的质量度量适用于不同的应用，例如作为基础设施质量度量或路由标准。