[2A5-GS-10] AI application: Traffic

[2A5-GS-10-04] Lightweight and High-Accuracy Inflow Traffic Volume Prediction for Traffic Flow Simulation

〇Naoya Nomoto¹, Takahiro Suzuki¹, Daisuke Okuya¹ (1. Oki Electric Industry Co., Ltd.)

Keywords:Time-series prediction, Traffic volume prediction, Traffic flow simulation, Seasonally adjusted model

We are researching traffic flow simulation using probe and traffic counter data to mitigate congestion and reduce accidents. Forecasting traffic volume is essential for this. Traditional methods like the seasonal adjustment model can predict hourly traffic volumes. However, for finer simulations, forecasting is required at shorter intervals. This becomes computationally challenging due to increased complexity in parameter adjustment. Our solution involves dividing the traffic volume data for training and forecasting, enabling predictions at shorter intervals while reducing computational complexity. The traffic flow simulations done using the predicted volumes were efficient in reproducing actual traffic flows.