由骑自行车的人,为骑自行车的人:道路等级和高度估计来自众包健身应用程序数据
Elmira Berjisian1, Alexander Bigazzi1, Hamed Barkh1
1Department of Civil Engineering, University of British Columbia, Vancouver, British Columbia, Canada.
PloS one
|December 20, 2023
概括
群众来源的GPS数据可以准确地估计行走和骑自行车分析的道路等级. 这种方法比高度模型更可靠,为积极的运输规划提供了可扩展的解决方案.
科学领域:
- 地理空间分析是什么?
- 运输工程 运输工程 运输工程
- 积极的运输研究 运输研究
背景情况:
- 道路等级显著影响步行和骑自行车的行为和结果.
- 精确的道路等级数据很少,阻碍了旅行信息和分析.
- 众包GPS数据为生成道路等级数据集提供了一个潜在的解决方案.
研究的目的:
- 检查群众来源的GPS数据的准确性,以估计道路等级配置文件.
- 验证和修改现有的路面等级分析的高度估计方法.
- 开发全网范围的道路等级数据集,以进行增强的旅行分析.
主要方法:
- 使用现场测量数据对高度估计方法的外部验证.
- 修改和评估道路等级估计方法.
- 群众来源的GPS数据的聚合使用分区-围绕-medoid集群,萨维茨基-戈莱过器和DBSCAN.
- 实现每个位置平均有150个GPS跟踪.
主要成果:
- 群众来源的GPS数据提供了相对准确的道路等级估计.
- 与其他数据源相比,等级估计比海拔估计更可靠.
- 最准确的方法实现了1%的路等级的根平均平方误差 (RMSE).
结论:
- 一个适度的群众来源的GPS数据可以产生准确的道路等级估计.
- 这种方法优于低分辨率的高度模型,但不如LiDAR衍生数据准确.
- 结果使得准确的道路等级信息可以纳入街道网络,用于积极的运输分析.
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