Measurement and analysis of pedestrian traffic characteristics in real time
DOI:
https://doi.org/10.24136/tren.2025.012Keywords:
traffic, pedestrian crossing, OpenCV, vision technique, attractiveness, POIAbstract
This article addresses the issue of measuring and analyzing pedestrian traffic characteristics in real time. The proposed methodology employs standard, low-cost web cameras, which are temporarily installed at selected pedestrian crossings in Katowice. In subsequent stages of the research, cameras will be deployed at signalized pedestrian intersections, with their locations optimized according to the adopted measurement procedures. In this context, the spatial positioning of the camera is a critical factor that affects the quality of data and the quality of the measurement. The primary objective of the measurements presented is to analyze pedestrian traffic dynamics within the framework of a conceptual model describing the interactions between pedestrian and vehicular flows, as well as interpersonal interactions among pedestrians at intersections, with and without traffic signals. Here are some concepts for using such a model. The theoretical model will be elaborated in future publications. The present article focuses on the development and implementation of the real-time automatic data acquisition method that supports this modeling approach. Real-time data collection was conducted using computer vision techniques implemented with the OpenCV library and the Python programming language. The software system operates on the Windows platform, but can be run on any platform: Unix, MacOS. In the analysis, a comprehensive set of traffic parameters was employed that accounts for both the spatial and functional characteristics of the observed environment, as well as the behavioral patterns of pedestrian movement.
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