modeling pedestrian flow in urban pedestrian facilities using meta-heuristic algorithms (Case study: Rasht city

مهندسی عمران فردوسی

Article 4, Volume 34, Issue 4 - Serial Number 36, November 2021, Pages 45-54   

Document Type: Original Article

DOI: 10.22067/jfcei.2022.73898.1088

Authors

Seyed Ebrahim Abdolmanafi Rokni^{* 1}; termeh vedadi²; Seyed Amir Saadatjoo³; Saeed Fatemi⁴; Seyed Ali Ziaee⁵

¹Department of Civil Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran

²Department of Civil Engineering, Islamic Azad University, Tehran North Branch, Tehran, Iran.

³Faculty of Civil Engineering, Iran University of Science and Technology

⁴Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

⁵Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

Abstract

Pedestrian behavior plays an important role in the design of pedestrian facilities, especially in high-traffic areas. One of these behavioral characteristics is the speed of their walking on sidewalks and sidewalks and the speed of crossing the width of urban thoroughfares at lighted intersections and marked crossings; Therefore, the most important step is to know the flow parameters of pedestrians when passing through various urban facilities. The aim of this study is to model the flow of pedestrians crossing various urban pedestrian facilities (sidewalks, sidewalks, intersections with and without lights). Therefore, by photographing a sidewalk and a sidewalk, a passage without lights and a crossroads with lights, 5031 pedestrian crossings were collected. Then, using regression models and genetic algorithm method, pedestrian flow relationships such as speed, flow rate and density were modeled. The results showed that the accuracy of the models for different facilities including sidewalks, sidewalks, lightless intersections and lighted intersections using genetic algorithm has a higher prediction accuracy than the regression method and is equal to 0.9451, 0.9062, 0.9682 and 0/9938 are; Therefore, in this field, genetic algorithm can be introduced as one of the meta-innovative methods that has more accuracy, as a superior model

Keywords

Pedestrian; speed; flow rate; regression; genetic algorithm method

Supplementary Files

CE(34-4)-4-abdolmanafi-Revised.pdf

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