Time Series Analysis for Traffic Flow Using Dynamic Linear Model


KIPS Transactions on Computer and Communication Systems, Vol. 6, No. 4, pp. 179-188, Apr. 2017
10.3745/KTCCS.2017.6.4.179,   PDF Download:
Keywords: BIS, DLM, Traffic
Abstract

It is very challenging to analyze the traffic flow in the city because there are lots of traffic accidents, intersections, and pedestrians etc. Now, even in mid-size cities Bus Information Systems(BIS) have been deployed, which have offered the forecast of arriving times at the stations to passengers. BIS also provides more informations such as the current locations, departure-arrival times of buses. In this paper, we perform the time-series analysis of the traffic flow using the data of the average trvel time and the average speed between stations extracted from the BIS. In the mid size cities, the data from BIS will have a important role on prediction and analysis of the traffic flow. We used the Dynamic Linear Model(DLM) for how to make the time series forecasting model to analyze and predict the average speeds at the given locations, which seem to show the representative of traffics in the city. Especially, we analysis travel times for weekdays and weekends separately. We think this study can help forecast the traffic jams, congestion areas and more accurate arrival times of buses.


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Cite this article
[IEEE Style]
K. H. Geun, P. C. Young, S. C. Sun, C. Y. Yun, P. J. Woo, "Time Series Analysis for Traffic Flow Using Dynamic Linear Model," KIPS Transactions on Computer and Communication Systems, vol. 6, no. 4, pp. 179-188, 2017. DOI: 10.3745/KTCCS.2017.6.4.179.

[ACM Style]
Kim Hong Geun, Park Chul Young, Shin Chang Sun, Cho Yong Yun, and Park Jang Woo. 2017. Time Series Analysis for Traffic Flow Using Dynamic Linear Model. KIPS Transactions on Computer and Communication Systems, 6, 4, (2017), 179-188. DOI: 10.3745/KTCCS.2017.6.4.179.