Bang Yoonsik, Kim Jiyoung, Yu Kiyun
Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea.
Sensors (Basel). 2016 Oct 22;16(10):1768. doi: 10.3390/s16101768.
Wearable and smartphone technology innovations have propelled the growth of Pedestrian Navigation Services (PNS). PNS need a map-matching process to project a user's locations onto maps. Many map-matching techniques have been developed for vehicle navigation services. These techniques are inappropriate for PNS because pedestrians move, stop, and turn in different ways compared to vehicles. In addition, the base map data for pedestrians are more complicated than for vehicles. This article proposes a new map-matching method for locating Global Positioning System (GPS) trajectories of pedestrians onto road network datasets. The theory underlying this approach is based on the Fréchet distance, one of the measures of geometric similarity between two curves. The Fréchet distance approach can provide reasonable matching results because two linear trajectories are parameterized with the time variable. Then we improved the method to be adaptive to the positional error of the GPS signal. We used an adaptation coefficient to adjust the search range for every input signal, based on the assumption of auto-correlation between consecutive GPS points. To reduce errors in matching, the reliability index was evaluated in real time for each match. To test the proposed map-matching method, we applied it to GPS trajectories of pedestrians and the road network data. We then assessed the performance by comparing the results with reference datasets. Our proposed method performed better with test data when compared to a conventional map-matching technique for vehicles.
可穿戴设备和智能手机技术的创新推动了行人导航服务（PNS）的发展。PNS需要一个地图匹配过程，以便将用户的位置投影到地图上。许多地图匹配技术已被开发用于车辆导航服务。但这些技术不适用于PNS，因为与车辆相比，行人的移动、停止和转弯方式不同。此外，行人的基础地图数据比车辆的更复杂。本文提出了一种新的地图匹配方法，用于将行人的全球定位系统（GPS）轨迹定位到道路网络数据集上。该方法的理论基础是弗雷歇距离，它是两条曲线之间几何相似性的度量之一。弗雷歇距离方法可以提供合理的匹配结果，因为两条线性轨迹是根据时间变量进行参数化的。然后我们改进了该方法，使其适应GPS信号的位置误差。基于连续GPS点之间自相关的假设，我们使用一个自适应系数来调整每个输入信号的搜索范围。为了减少匹配中的误差，实时评估每个匹配的可靠性指标。为了测试所提出的地图匹配方法，我们将其应用于行人的GPS轨迹和道路网络数据。然后，我们将结果与参考数据集进行比较，以评估其性能。与传统的车辆地图匹配技术相比，我们提出的方法在测试数据上表现更好。
