The understanding of the mobility on urban spaces is useful for the creation of smarter and sustainable cities. However, getting data about urban mobility is challenging, since only a few companies have access to accurate and updated data, that is also privacy-sensitive.

In this work, we characterize three distinct car-sharing systems which operate in Vancouver (Canada) and nearby regions, gathering data for more than one year. Our study uncovers patterns of users’ habits and demands for these services. We highlight the common characteristics and the main differences among car-sharing systems. Finally, we believe our study and data is useful for generating realistic synthetic workloads.

对城市空间流动性的理解对于创建更智能和可持续发展的城市非常有用。但是，获取有关城市交通的数据具有挑战性，因为只有少数几家公司可以访问准确且更新的数据，这对隐私也很敏感。

在这项工作中，我们描述了三种不同的汽车共享系统，它们在温哥华（加拿大）和附近地区运行，收集了一年多的数据。我们的研究揭示了用户习惯和对这些服务的需求的模式。我们重点介绍了汽车共享系统之间的共同特点和主要区别。最后，我们相信我们的研究和数据对于生成现实的综合工作负载很有用。