Hybrid time series forecasting methods for travel time prediction

Faruk Serin, Yigit Alisan and Adnan Kece

Physica A: Statistical Mechanics and its Applications, 2021, vol. 579, issue C

Abstract: Providing accurate information about travel time to passengers is important in public transportation. In this aspect, the travel time of buses between two consecutive stops can be handled as time series. Then, the future travel time can be predicted using time series forecasting methods. In this study, we propose a novel method with three-layer architecture to predict bus travel time between two stops. In the first layer of the proposed method, initial prediction is made by processing measured data. In the second layer, residuals are predicted in the specified depth. In the third layer, the final prediction is made by integrating the results of two previous layers with three different approach. The experiments were performed on the data, which were obtained from public transportation of Istanbul, using various time series forecasting methods in form of traditional and proposed architecture. The results show that proposed method outperforms traditional approach with approximately MAPE of 6.

Keywords: Bus arrival time; Prediction; Public transportation; Time series models; İstanbul (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:579:y:2021:i:c:s0378437121004076

DOI: 10.1016/j.physa.2021.126134

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