Research And Development On Multi-source Traffic Data Automated Collecting And Processing System

Road transportation is a vital infrastructural support for China economy ecosystem, bearing the tasks of personnel and materials transportation around our country. With the rapid development of transportation informationalization process, the need to collect and make usage of transportation data for a variety of tasks, becomes urgent for operation management and related research works in China road transportation. For this reason, an automated collecting and processing system for multi-source traffic data, with major functionalities as data collection, transmission, storage, demarcation and processing, was designed and implemented in this dissertation. This system is applicable for a variety of transportation data collection tasks in, and can provide abundant data for, many practice and research works in areas such as operation management, traffic monitoring, traffic flow regulation and control, etc. The major works of this dissertation are as follows:(1) By analyzing and summarizing different categories, collecting and processing methods, and application requirements of multi-source traffic data, a multiple layered framework of automated multi-source traffic data collecting and processing system was constructed, and the data transmission protocols between adjacent layers were designed.(2) Based on embedded ARM platform, the lower end data collecting subsystem was devised. In this subsystem, the peripheral circuit is built around an ARM S3C2440 chip, the kernel software program is composed with loose-coupled plugins, therefore providing functionalities as data collecting, data caching, and data transmission.(3) After summarizing the functionality hierarchy, major modules and key business processes, the upper end software subsystem was developed on MS.NET platform. It implements the functionalities as inter-subsystems communication, demarcation management, data storage, data computation, and so on. Demonstration application showed that, our system runs stably, and is quite applicable for multi-sourced transportation data collection.