Research On Technologies Of Public Transportation Navigation Service System With Travel Time Prediction

This paper analyzes the status of domestic and foreign urban public transport intelligent systems development, the mode of urban public transportation service system service, and finds that the navigation system of urban public transport with travel time prediction is a current open issue in the field of intelligent transportation, which is to alleviate traffic pressure and is important to promote green travel.For the Navigation system for urban public transport travel time characteristics of timeliness, this paper reviews the existing travel time prediction models. It uses GPS-based probe vehicle travel time acquisition methods, and then studies data preprocessing of travel time and average travel time model the line Travel time model, statistical analysis of the sample characteristics of travel time, respectively. Finally it innovatively puts forward for a probabilistic travel time prediction model based on statistical analysis, which is applicable to urban public transport navigation systems. Thus, it provides a new way for travel time prediction.This study shows that the sample population mean is subjected to Normal distribution. The confidence level and interval of the sample population mean, the probability distribution in the certain status analysis time period of day, will be both the predicted information. In this paper, bus routes of the typical large and medium cities in China and the general and BRT travel time prediction cases are studied in order to verify and demonstrate that the proposed travel time probability model is feasible and reliable.Finally, based on Java EE, EJB architecture and XML middleware platform, the paper implements PTNS-Engine, PTNS-QAS software platform of the urban public transport navigation system based Client/Server architecture.