Park Chul Young, Kim Hong Geun, Shin Chang Sun, Cho Yong Yun, Park Jang Woo

KIPS Transactions on Computer and Communication Systems, Vol. 6, No. 7, pp. 297-306, Jul. 2017
10.3745/KTCCS.2017.6.7.297,   PDF Download:
Keywords: Bus Information System, Arrival Time Estimation, Service Time Estimation, Hidden Markov Model, Generalized Additive Model
Abstract

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

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