Abstract
The road capacity in winter in Sapporo is decreased as a result of certain snow removal operations and increased as a result of other operations, and the average travel speed in winter is slower than in autumn. Cyber-physical systems allow us to collect valuable data, such as traffic and weather data, from advanced sensors. Many researchers have used these data in their studies. This study estimates travel speed toward forecasting winter traffic congestion in Sapporo. Four steps are performed to estimate the travel speed, considering the relationships among traffic, weather and snow removal factors. The first step is to collect data and to set up the dataset. The second is to develop multiple linear regression models, and the next is to predict residuals between observed and estimated travel speed by MLR model, using SARIMA. Finally, the estimated travel speed is presented as the results of MLR model and SARIMA.
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