Abstract
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.
Highlights
In recent years, consumption and logistics patterns have changed with the development of economies and the gradual increases in national incomes
Parallel computing and cloud computing techniques are designed into the proposed mobile positioning method to quickly determine the location of an on-board unit (OBU) for commercial vehicle operation (CVO)
This study proposes analytical models to analyze the availability of the proposed mobile positioning method with different outlier filtering criteria
Summary
Consumption and logistics patterns have changed with the development of economies and the gradual increases in national incomes. The Global Positioning System (GPS) is the most popular location determination method for OBUs [1]. This paper considers mobile positioning techniques to obtain location information when the signals of GPS satellites are weak. Various techniques have been proposed to analyze the signals from radio frequency identification (RFID) [2], Bluetooth [3], wireless local area networks (WLAN) [4,5,6], wireless sensor networks (WSN) [7,8], and cellular networks [9] for location determination [10]. This study proposes a high-efficiency mobile positioning method to analyze the cellular network signals of CVO data.
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