Research And Design Of Center Navigation Algorithm Based On Multi-Source Information Fusion

With the rapid changing development of modern techniques and the increasing complicated of urban road constructs, automobiles have served as the necessary vehicle in people’s daily life. Unfortunately, come along with it are traffic jams which are becoming extraordinarily troubling and bothering things. Thus, a set of robust and auto smart manage system, which can allocate the traffic flow reasonably and rationally, balance the load efficiently, make considerable and meaningful strategies for citizens, is acutely required. Intelligent transportation systems, a kind of comprehensive traffic intelligent management system with high veracity, efficiency and real-time capability, are proposed in this context to control the traffic network in a global range by taking advantage of the GPS technology, digital communication technology, computer technology and information processing technology. Being an important part of the intelligent transportation system.Vehicle navigation system, having a research history as long as several decades, it has two forms: autonomous navigation system and central navigation system. Both of them have the same function and similar structure. The main difference of them lies on the responsibility division: the autonomous navigation system, having a tendency to storage large amount of information and do computing at local and having a high requirement for hardware, the most widely used and mature system in recent days; the central navigation system analyzes and processes the urban real-time traffic and information at the center service, and then provide citizens with dynamic and real-time navigation service, which, to a high degree, meets the users’ demand for travel efficient, convenient, fast. The demand of central navigation system is increasing. This paper’s research is based on this background and combined with actual project.The road weight computing and the center navigation algorithm are the key technology of central navigation system. Therefore, this paper focused on these two aspects. The road weight computing eliminated the invalid data points provided by the taxi driving by analyzing the features of CAN data information and GPS data information. Then, it fuses the data information such as travel time, energy losses and electronic maps, to get the various road weights, which serve as the input parameters of path planning algorithm. The center navigation algorithm contains map matching algorithm and path planning algorithm. Because GPS exists somewhat error, the map matching algorithm is mainly used to revise the GPS Points acquired via the flo ating cars. This paper proposed revised map matching algorithm which combined the scratchable latex model, vehicle track analysis model, and weight computing model. It has a good performance through experiments. The path planning algorithm is designed to an algorithm that takes the traffic rules constraint into consideration. It solves the incorrect plan problem when add traffic information constraint into the road network. Finally, the feasibility of the algorithm is verified by experiments.