篇名：A High-Efficiency Method of Mobile Positioning Based on Commercial Vehicle Operation Data
作者：Chi-Hua Chen*(陈志华), Jia-Hong Lin, Ta-Sheng Kuan, Kuen-Rong Lo
来源：ISPRS International Journal of Geo-Information
年份：2016
DOI: 10.3390/ijgi5060082
文章摘要：
Commercial vehicle operation (CVO) has been a popular application of intelligent transportation systems. Location determination and route tracing of an on-board unit (OBU) in a vehicle is an important capability for CVO. However, large location errors from global positioning system (GPS) receivers may occur in cities that shield GPS signals. Therefore, a highly efficient mobile positioning method is proposed based on the collection and analysis of the cellular network signals of CVO data. Parallel- and cloud-computing techniques are designed into the proposed method to quickly determine the location of an OBU for CVO. Furthermore, this study proposes analytical models to analyze the availability of the proposed mobile positioning method with various outlier filtering criteria. Experimentally, a CVO system was designed and implemented to collect CVO data from Chunghwa Telecom vehicles and to analyze the cellular network signals of CVO data for location determination. A case study found that the average errors of location determination using the proposed method vs. using the traditional cell-ID-based location method were 163.7 m and 521.2 m, respectively. Furthermore, the practical results show that the average location error and availability of using the proposed method are better than using GPS or the cell-ID-based location method for each road type, particularly urban roads. Therefore, this approach is feasible to determine OBU locations for improving CVO.
商用车运营（CVO）已成为智能交通系统的一个热门应用。车载设备（OBU）的位置确定和路径跟踪是CVO的一项重要功能。然而，在屏蔽GPS信号的城市中，全球定位系统（GPS）接收机可能会产生较大的定位误差。因此，提出了一种高效的移动定位方法，该方法基于对CVO数据蜂窝网络信号的采集和分析。并行计算和云计算技术被设计到该方法中，用于快速确定CVO的OBU位置。此外，本研究提出了分析模型，以分析所提出的移动定位方法在各种离群值过滤标准下的可用性。在实验上，设计并实现了一个CVO系统，用于收集来自中华电信车辆的CVO数据，并分析CVO数据的蜂窝网络信号以确定位置。一个案例研究发现，与传统的基于小区ID的定位方法相比，使用该方法进行定位的平均误差分别为163.7 m和521.2 m。此外，实际结果表明，对于每种道路类型，尤其是城市道路，使用该方法的平均定位误差和可用性优于使用GPS或基于小区ID的定位方法。因此，这种方法是可行的，以确定OBU的位置，以改善CVO。
