Estimation of Traffic Volume by Optimizing Mixture Distributions

Abstract

The evolutionary computation competition in 2022 introduced an estimation task of traffic volume of pedestrians by using simulation. This task requires participants to estimate the departure time and the number of people of three types of pedestrians (slow, busy, guided), respectively. In this report, we propose to model traffic volume as a mixture distribution and to optimize the center point, width, strength, distribution type, and the width of Gaussian filter by using evolutionary computation algorithms. For one of the single objective optimization problems, our methods came second, which shows the effectiveness of our proposed method.