Integration of Rural Terrain Data for Optimal Path Finding

整合农村地形数据以寻找最佳路径

• 批准号: 2097059
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2097059
• 关键词: Integration; Rural; Terrain; Data; Optimal

The research will look at methods to integrate a range of large-scale terrain data, and combine it to plan the fastest safe path back to a road from any point.Many different data sources are available, such as terrain height, topography and flood risk, as well as user-generated hiking routes showing known paths. These are available in varying resolutions and accuracies for different regions. As well as this, other less tangible data sources can be considered, such as the ability and condition of the walking group. Initially, the maximal extent of data will be used to produce a terrain analysis which is as accurate as possible, i.e. the nearest thing we can have to a ground truth. Once a terrain map has been created, path/route planning algorithms will be used to find the shortest safe path over very large areas to a non-specific location. Following this, the impact of removing different data layers and the impact of adding noise can then be simulated to determine the most informative features when analysing terrain to create a navigable route. Furthermore, it should be possible for the results to be amended with the addition of live inputs such as weather conditions, or time of day.Finally, as a practical outcome of the project I aim to use these findings to produce a navigational aide, it would be beneficial if the results could be accessed offline. This will require being able to store and query maps directly on a device, adding data storage and optimisation challenges to the project. Work will be required to decide how much pre-computation of the data can be performed, and for the live updates whether it is possible to run these calculations on the device, or whether all possible combinations of solutions should be stored on the device, and the relevant results displayed.

该研究将着眼于整合一系列大规模地形数据的方法，并将其结合起来，以规划从任何点返回道路的最快安全路径。有许多不同的数据源可用，例如地形高度、地形和洪水风险，以及用户生成的显示已知路径的徒步旅行路线。在不同的地区，这些工具有不同的分辨率和精度。除此之外，还可以考虑其他不太有形的数据来源，例如步行组的能力和状况。最初，最大范围的数据将用于生成尽可能准确的地形分析，即我们可以拥有的最接近地面真相的东西。一旦创建了地形图，路径/路线规划算法将用于在非常大的区域内寻找到非特定位置的最短安全路径。在此之后，可以模拟去除不同数据层的影响和添加噪声的影响，以确定在分析地形以创建可通航路线时最具信息量的特征。此外，应该可以通过添加实时输入（如天气条件或一天中的时间）来修改结果。最后，作为项目的一个实际成果，我的目标是使用这些发现来生成导航助手，如果结果可以离线访问，那将是有益的。这将需要能够直接在设备上存储和查询地图，这给项目增加了数据存储和优化方面的挑战。需要决定可以执行多少数据的预计算，以及对于实时更新是否可以在设备上运行这些计算，或者是否应该将所有可能的解决方案组合存储在设备上，并显示相关结果。