Bock Fabian, Di Martino Sergio
Institute of Cartography and Geoinformatics, Leibniz University, Hannover, Germany.
Department of Electrical Engineering and Information Technologies, University of Naples "Federico II", Naples, Italy.
Data Brief. 2019 Jun 4;25:104039. doi: 10.1016/j.dib.2019.104039. eCollection 2019 Aug.
This dataset contains records of the measured on-street parking availability in San Francisco, obtained from the public API of the project. In 2011, the San Francisco Municipal Transportation Agency (SFMTA) started a project on smart parking, called , whose goal was the improvement of on-street parking management in San Francisco, mostly by means of demand-responsive price adjustments [1]. One of the key points of the project was the collection of information about on-street parking availability. To this aim, about 8,000 parking spaces were equipped with specific sensors in the asphalt, periodically broadcasting availability information. The SFpark project made available a public REST API, returning the number of free parking spaces and total number of provided parking spaces per road segment, for 5,314 parking spaces on 579 road segments in the pilot area. We collected parking availability data from 2013/06/13 until 2013/07/24, by querying this API at approximately 5-min intervals. As a result, we obtained in total about 7 million observations of parking availability on the road segments. These observations represent the first dataset we are providing. In addition, we simulated the achievable sensing coverage of on-street parking availability that could be achieved by a fleet of taxis, if they were equipped with sensors able to detect free parking spaces, like side-scanning ultrasonic sensors [3], or windshield-mounted cameras [4]. In particular, by exploiting real taxi trajectories in San Francisco from the Cabspotting project [5], we first computed the frequencies of taxi visits for each road segment covered by the SFpark sensors. Then, we downsampled the first dataset, in order to have a parking availability information for a road segment at a given time only in presence of a transit of a taxi on that segment at that time. This step was replicated for 5 different sizes of taxi fleets, namely 100, 200, 300, 400, and 486. Consequently, in total six datasets are available for further research in the field of on-street parking dynamics. All these datasets can be downloaded at: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YLWCSU.
该数据集包含从该项目的公共应用程序编程接口（API）获取的旧金山路边停车位实测记录。2011年，旧金山市交通局（SFMTA）启动了一个名为“SFpark”的智能停车项目，其目标主要是通过需求响应式价格调整来改善旧金山的路边停车管理[1]。该项目的一个关键点是收集路边停车位可用性信息。为此，约8000个停车位在沥青路面安装了特定传感器，定期广播可用性信息。SFpark项目提供了一个公共REST API，可返回试验区579个路段上5314个停车位的空闲停车位数量和提供的停车位总数。我们从2013年6月13日至2013年7月24日，以大约5分钟的间隔查询此API，收集停车位可用性数据。结果，我们总共获得了约700万条路段停车位可用性观测数据。这些观测数据代表了我们提供的第一个数据集。此外，我们模拟了如果出租车车队配备能够检测空闲停车位的传感器，如侧扫超声波传感器[3]或安装在挡风玻璃上的摄像头[4]，所能实现的路边停车位可用性传感覆盖范围。具体而言，通过利用来自Cabspotting项目[5]的旧金山真实出租车轨迹，我们首先计算了SFpark传感器覆盖的每个路段出租车访问频率。然后，我们对第一个数据集进行下采样，以便仅在某路段某一时刻有出租车经过时，才获取该路段该时刻的停车位可用性信息。对5种不同规模的出租车车队（即100、200、300、400和486）重复此步骤。因此，总共有六个数据集可用于路边停车动态领域的进一步研究。所有这些数据集均可在以下网址下载：https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YLWCSU 。
