ParkNet: drive-by sensing of road-side parking statistics
ParkNet: drive-by sensing of road-side parking statistics
复制标题
DOI：
10.1145/1814433.1814448
复制
发表时间：
2010-06
期刊：
影响因子：
--
通讯作者：
Suhas Mathur;Tong Jin;Nikhil Kasturirangan;J. Chandrasekaran;Wenzhi Xue;M. Gruteser;W. Trappe
中科院分区：
文献类型：
--
作者：
Suhas Mathur;Tong Jin;Nikhil Kasturirangan;J. Chandrasekaran;Wenzhi Xue;M. Gruteser;W. Trappe
实时获得城市街道停车可用性统计数据具有挑战性，但通过减少交通拥堵将极大地造福社会。在本文中，我们介绍了 ParkNet 的设计、实现和评估，这是一个由车辆组成的移动系统，可以在行驶时收集停车位占用信息。每辆 ParkNet 车辆都配备了 GPS 接收器和面向乘客的超声波测距仪，用于确定停车位占用情况。数据聚集在中央服务器上，该服务器构建了停车可用性的实时地图，并可以将该信息提供给查询系统以搜索停车位的客户端。创建精确的停车位地图挑战了 GPS 定位精度的限制。为了满足这一需求，我们设计了一种环境指纹识别方法来提高定位精度。根据 2 个月内收集的 500 英里路边停车数据，我们发现停车位计数的准确率达到 95%，占用地图的准确率可以达到 90% 以上。最后，我们量化了在城市中提供足够覆盖范围所需的传感器数量。通过使用 500 多辆旧金山出租车的广泛 GPS 轨迹，我们发现，如果将 ParkNet 部署在城市出租车中，所产生的移动传感器将提供足够的覆盖范围，并且与在每个停车位配备专用传感器的传感器网络（目前正在旧金山进行测试）相比，其成本效益估计提高约 10-15 倍。
Urban street-parking availability statistics are challenging to obtain in real-time but would greatly benefit society by reducing traffic congestion. In this paper we present the design, implementation and evaluation of ParkNet, a mobile system comprising vehicles that collect parking space occupancy information while driving by. Each ParkNet vehicle is equipped with a GPS receiver and a passenger-side-facing ultrasonic range-finder to determine parking spot occupancy. The data is aggregated at a central server, which builds a real-time map of parking availability and could provide this information to clients that query the system in search of parking. Creating a spot-accurate map of parking availability challenges GPS location accuracy limits. To address this need, we have devised an environmental fingerprinting approach to achieve improved location accuracy. Based on 500 miles of road-side parking data collected over 2 months, we found that parking spot counts are 95% accurate and occupancy maps can achieve over 90% accuracy. Finally, we quantify the amount of sensors needed to provide adequate coverage in a city. Using extensive GPS traces from over 500 San Francisco taxicabs, we show that if ParkNet were deployed in city taxicabs, the resulting mobile sensors would provide adequate coverage and be more cost-effective by an estimated factor of roughly 10-15 when compared to a sensor network with a dedicated sensor at every parking space, as is currently being tested in San Francisco.