Kousei FUJITA
A Study on Prediction of a Road Surface Temperature and Traffic Speed by the Neural Network
Teruhiko MARUYAMA
In this study, we aimed improvement of the prediction accuracy, and proposed the new standard of snow removing as result of reflecting user's intention.
We previously reported that predicting traffic speed and road surface temperature in the cold area, by using neural network method. Whereas we recognize the importance of predicting and understanding those elements for road management in winter season,
It has not arrived to make the standard of snow removing included to use the data of the observation device.
By examining the result of thermal map closely, we extracted parts where road temperature is low, originates in a peripheral structure and geographical features. It is a place where the speed decreases exactly by the potential hazard. In these parts, it was needed to change expression that calculates RMSI.
In summary, We added the concept of gpotential hazardh to RMSI(Road Maintenance Service Index), proposed the new standard of snow removing.