支持人工智能解决方案解决停车问题

作者：Linda Duffy

随着有限数量的停车位和越来越多的汽车，与停车相关的挫败感和不便正在增长。认为这是一个问题，Manuela Rasthofer，首席执行官Terraloupe GmbH, launched a project to combine artificial intelligence and orthorectified aerial imagery to create an accurate inventory of available parking lots and spaces throughout Germany.

映射可用的停车位

停车汽车可能是一项压力且耗时的活动，将来，自动导航的车辆将在没有驾驶员提供帮助的情况下寻找空间。需要准确测量和识别所有类型的物体（包括停车位）的高清数字地图的需求迅速成为现实。

Terraloupe GmbH是一家位于德国慕尼黑的技术初创企业，专注于以创新的方式将Geodata和计算机分析相结合。从高分辨率矫形器开始，Terraloupe应用机器学习算法来检测和测量物理世界中的对象，例如建筑物，道路和树木，以创建数据丰富的3D模型。

“To address the growing parking problem, we wanted to see if it was feasible to detect and assess parking lots using aerial imagery and artificial intelligence,”Rasthofer说。“By automating the extraction of features and digital content, we thought we could greatly reduce the time it took to create maps, without sacrificing the accuracy.”

创建数字地图的一种经济高效的方法对于一级汽车供应商和原始设备制造商（OEM）特别有趣，以支持自主导航行业。但是，许多其他行业也可以利用这些信息。

HxGN Content Program delivers

Semantic lane model created out of detected lane markings based on 15 centimetres GSD data in Martinsburg

In 2014, theHxGN Content Programbegan collecting speculative off-the-shelf orthorectified imagery of the US, parts of Europe, and populated areas of Canada to create a database available to customers. The goal was to acquire cloud-free 30-cm resolution, 4-band imagery over less populated areas, and 15-cm resolution over metro areas with a population greater than 50,000.

通过HXGN Content计划，Terraloupe获得了15 cm的柏林分辨率，以测试其内部开发的对象识别算法。柏林的最初工作花了八周的时间来训练算法，以准确识别和分类停车位，然后仅三天来分析和制作整个德国的地图。

“Access to imagery through the HxGN Content Program allows us to download the geographic locations we need, and then train our algorithms on the new data,”Rasthofer解释了。“每个国家 /地区独有的建筑，基础设施和道路系统总是有轻微的差异。我们检查每个对象的置信区间，并重新检查低百分比。当我们纠正错误时，算法继续学习和改进，直到达到非常高的准确性水平为止。”

通过HXGN Content计划获得的空中矫形图会通过严格的QA/QC过程，以确保传递调查级图像。“The HxGN Content Program best suits the needs of our customers in the areas of autonomous driving, parking assistance, and loss reports for insurance/reinsurance companies,”Rasthofer说。“我们还成功地提供了与基础设施，公用事业，铁路和其他有关各种目的有关的情报。”

accurate mapping

TerraLoupe’s project shows that high-resolution aerial orthoimages combined with machine learning can effectively be used to extract digital content. The parking analysis provides useful information, such as the locations, entrances and exits of parking lots and the number of cars of different categories (compact, medium-sized, large) that can fit in each lot. Urban planners, delivery people, taxi drivers, and patrons in congested retail areas could all benefit from this improved parking intelligence.

“高分辨率，高准确图像的可用性决定了我们在哪里开始该项目；但是，我们打算在整个欧洲进行此分析，因为数据通过Hexagon获得，我们希望将服务扩展到美国，”bob体育报道Rasthofer说。“Overall our goal is to efficiently extract all types of objects and create a complete digital environment.”

Obtaining aerial imagery is faster and more efficient than terrestrial methods, allowing more frequent updates, which is crucial for many applications. Hexagon’s global operations generate widespread availability of imagery and good business partnerships with data providers to continue to meet the growing demand for digital maps.