Research On The Methods Of Analyzing The City Real-time Traffic Condition Based On The Data Of The Front Surveillance Video And GPS Of Bus

With the development of the new generation of information technologies, in order to utilize the information technologies to promote the development of cities, the Intelligent City has become the research hot topic all around the world. Since the transportation system is the important part of city, the Intelligent Transportation System becomes the vital project of construction of city. Intelligent Transportation System is to apply the Internet of Things, Cloud Computing, the Sensor Technology and the mobile network technology to the transportation system to solve the transportation issues of city and improve the service level of transportation system. In recent years, the service level of the transportation system has greatly been improved following the development of the Intelligent Transportation System. However, there are many problems in the transportation system, such as the traffic jam and lacking of an efficient city path navigation. How to use the new generation of information technologies to tackle the problems in the transportation system is an important research topic of the Intelligent Transportation System, and also is significant for bettering the traffic condition of city.This paper utilizes the present hardware resources and software resources of the Intelligent Transportation System, combining with the computer technology, the mobile technology, Cloud technology and the video-analyzing technology, and proposes a series of methods to solve the problems in the transportation system. Firstly, use the resources of the Intelligent Bus System to propose the method of detecting the real-time traffic condition of city, and then utilize the information of the real-time traffic condition to propose the algorithm of city path navigation. The main topics contain:(1) The current technologies of sensing the real-time traffic condition are compared and studied, and their disadvantages are pointed out. The road network representation methods and the optimal path selection algorithms are researched, which are related to the city path navigation.(2) Combining the Cloud technology and the Supercomputer Center, a cloud platform of Intelligent Bus System is proposed. The cloud platform is studied from three aspects: collecting information, processing data and application and service.(3) On the basis of the Cloud Platform, the front surveillance video and GPS data are used to propose a real-time traffic condition detection technology respectively, and according to the variation of road environment, different detection technologies are utilized to propose the city real-time traffic condition detection method. During the procedure, the bus real-time text data are used to propose a bus real-time location technology.(4) Different optimization methods are utilized in the road network representation, the computing of road weight and the optimal path selection algorithm, and propose the city path navigation algorithm based on the time. The algorithm utilizes the dynamic information and the static information of road, and mixes the dynamic path navigation algorithm and the static path navigation algorithm.(5) The data of the Intelligent Bus System and the computer vision library are used to design experiments to verify and analyze the methods and technologies proposed in this paper.