Abstract
Bus transportation service is more strongly influenced than other public transport modalities by various factors such as traffic congestion, weather conditions, number of passengers, and traffic signals. These factors often cause delays, and users may feel inconvenienced when waiting at a bus stop. Few studies have analyzed the relationship between operational situations and multiple different factors by visualization. Thus, we propose an arrival time estimation method and a visualization model. The arrival time estimation model dynamically updates the accuracy via an estimation method using a combination of a multiple-regression model and a Kalman filter. The visualization model analyzes relationships between delays and various factors. The goal of this study is to realize a society where people can use buses more comfortably.
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Acknowledgements
We wish to thank Meitetsucom Co. Ltd and Meitetsu Bus Co., Ltd for insightful suggestions and provision of bus traffic data. This research and development work was supported by the JST OPERA and the MIC/SCOPE #172106102.
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Hiroi, K., Imai, H., Kawaguchi, N. (2019). Dynamic Arrival Time Estimation Model and Visualization Method for Bus Traffic. In: Mine, T., Fukuda, A., Ishida, S. (eds) Intelligent Transport Systems for Everyone’s Mobility. Springer, Singapore. https://doi.org/10.1007/978-981-13-7434-0_9
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DOI: https://doi.org/10.1007/978-981-13-7434-0_9
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