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

[2A5-GS-10-02] Parameter Estimation for Model of Traffic Flow Simulation by Using Data Assimilation

〇takahiro suzuki¹, kengo okano¹, hideki fujii², daisuke okuya¹ (1. Oki Electric Industry Co., Ltd, 2. The University of Tokyo)

Keywords:Traffic flow simulation, Data Assimilation, Probe data

We aim to realize smooth traffic flow to solve social issues in transportation, such as traffic congestion and accidents. We can verify traffic measures virtually to achieve smooth traffic flow by using traffic flow simulation. The virtual verification allows making decision on traffic measures efficiently and cost-effectively. On the other hand, the precision of the simulation must be high for using simulation effectively. Then it is important to set appropriate parameters for the simulation model. However, appropriate parameters are rarely known in advance, and they have often been determined by trial and error. In this study, we statistically estimate the parameters using traffic probe data through a data assimilation method called the ensemble Kalman filter. We determined the parameters for testing from the estimated parameters of each date. In the results of the Traffic flow simulations with the determined parameters, they reproduced traffic flow close to actual one.