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A Bus Arrival Time Prediction Method Based on GPS Position and Real-Time Traffic Flow

Time-of-arrival estimation is a key issue in the field of intelligent transportation research. In general, corresponding techniques are designed based on Global Positioning System (GPS) data. Unfortunately, the low precision of bus-mounted GPS system and lack of real-time traffic information lead to low estimation accuracy - greatly influence bus service performance. In this paper, a GPS calibration method is put forward, while projection rules of specific road shapes are discussed. Moreover, a real-time traffic evaluation algorithm is given. Then a hybrid dynamic prediction model, which achieves accuracy enhancement by taking into account traffic flow evaluation results and GPS position calibration, is proposed to predict the bus arrival time. Bus stop positions are used as reference points to verify effectiveness of proposed method. Bus data set is used to test effectiveness of proposed method. Test results demonstrate that our technique can provide a higher level of accuracy compared to methods based on traditional time-of-arrival techniques.