Modeling of Pedestrian Flow Density in Signalized Intersections Using Fuzzy Method (Case Study: Rasht City)

Abstract

Signalized intersections are among the facilities where pedestrians may have collisions with vehicles, which can lead to serious injuries and damages, and ultimately a severe reduction in network capacity. For this reason, recognizing the behavioral characteristics of pedestrians is the most important element in designing intersections and pedestrian facilities. The purpose of this study is to model the flow of pedestrians at signalized intersections. Therefore, by investigating two signalized intersections in Rasht city, Iran, data of 8277 pedestrians were collected and then the flow of pedestrians was modeled using fuzzy method. The results showed that the crosswalk crossing conditions by moving a higher flow rate compared to non-crossing areas are more suitable and desirable for pedestrians. The results also indicated that in the conditions of crossing from crosswalks and unauthorized areas, the superior models have R 2 of 80.88% and 90.68%, respectively, and the input and output membership function algorithm was Gaussian which has 4 membership functions for each of the inputs to predict the density values in the total intersections.