The Research Of Bus Real-Time Forecast Arrival Model Based On GPS

Public transport system has an irreplaceable role in the mitigation of urban traffic, and it can effectively improve the operating efficiency of road traffic system and service ability of urban residents. As a city resident, it is very concerned about the arrival time of public vehicles, the arrival time can reduce the waiting time in the platform, improve the passenger car satisfaction, but also optimize the passenger travel plan, so as to improve the level of public services. In recent years, many countries are aware of the importance of public transport information release, bus arrival time prediction plays an important role in the application of intelligent public transport technology, the relevant forecasting and information dissemination system is widely used in many places.First of all, this paper introduces the intelligent bus system bus arrival time related research background, in the application process is encountered some problems to be solved based on the study of exhibition format, and the generality of the introduction to the current intelligent public transportation system in bus arrival time prediction and the development of the workSecondly, the structure of the GPS system is introduced, and then the GPS structure is analyzed. The reasons of the GPS error are analyzed, and the solutions are given in the following sections. GPS data acquisition and preprocessing is the basis and premise of the bus arrival time prediction model. It is also a key technology to realize the accurate prediction of bus arrival time.In spite of the influence of various factors, we can see that the running time of the bus is still a certain regularity in the historical data. However, for the same bus lines on the bus, if there is a sudden traffic situation, the travel time will have a certain deviation, if only rely on historical data, or there may be a certain deviation. But the average instantaneous speed of the front vehicle (current traveling vehicle) is the important reference factor of the traffic condition of the road, and the data acquisition and preprocessing are evaluated and modified.Finally, the experiment chose the Nanchang high rail on the 2nd line prediction experiment, the bus line after the two important area of Nanchang City, West Rail Station, traffic is relatively complicated road, very representative. The results prove that the accuracy and reliability of the model meet the practical requirements.