| Abstract |
With the proposal of the theory of “smart city”, the public transportation travel information service is facing the requirement of higher quality, and the optimization of the traffic data used to support the travel information service in the process of collection and processing is the key and difficult point. In view of the current data source used to support the public transportation information service calculation to the calculation only based on bus GPS data, and the data source data less, long sampling interval, road calculation accuracy is low, combined with the current traffic information fill and data fusion technology research and development, in the analysis of bus data and taxi data commonness and characteristics, the rule of historical data and the connection between real-time data, puts forward a set of based on traffic information to fill and data fusion algorithm for bus arrival time provide data support prediction. Through the actual operation data test, the data fusion algorithm proposed in this paper reduced the average relative error of bus travel time by 8%, introduced the traffic information filling model and data fusion model into the specific bus arrival system for actual test, and the final prediction accuracy reached 86.27 and 7. 09%. The above experimental data show that the proposed method has significant advantages and good applicability over the existing methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. |
