Estimation method of traffic volume using big-data

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Abstract

Traffic jams have recently become a significant problem in provincial cities that tend to have poor railway services in Japan. Therefore, the main means of transportation are public buses, taxies, and private vehicles. Moreover, traffic accidents and road construction sites frequently block traffic. It is therefore difficult to estimate the travelling time from the origin to destination in real-time. To estimate the travelling time, we must predict the behaviors of many vehicles that depend on an “origin to destination” (OD) traffic volume. In our previous study, we proposed an estimation method for OD traffic volume using two types of big data, a road traffic census and mobile spatial statistics. In this study, we evaluated our proposed method on various situations through a traffic simulation.

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Someya, K., Kiyohara, R., & Saito, M. (2020). Estimation method of traffic volume using big-data. In Advances in Intelligent Systems and Computing (Vol. 1036, pp. 387–395). Springer Verlag. https://doi.org/10.1007/978-3-030-29029-0_36

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