Microscopic Pedestrian Flow Characteristics: Development of an Image Processing Data Collection and Simulation Model
Kardi Teknomo

TL;DR
This paper develops image processing tools and a simulation model to analyze microscopic pedestrian flow, providing insights into pedestrian behavior, flow characteristics, and policy evaluation through validated data and experiments.
Contribution
It introduces new image processing systems and a physical-based simulation model for microscopic pedestrian flow analysis, validated with real-world data.
Findings
Pedestrian speeds follow a normal distribution with mean 1.38 m/sec.
Acceleration distribution resembles a normal distribution with mean 0.68 m/sec².
Simulation effectively predicts pedestrian behavior and evaluates crossing policies.
Abstract
Microscopic pedestrian studies consider detailed interaction of pedestrians to control their movement in pedestrian traffic flow. The tools to collect the microscopic data and to analyze microscopic pedestrian flow are still very much in its infancy. The microscopic pedestrian flow characteristics need to be understood. Manual, semi manual and automatic image processing data collection systems were developed. It was found that the microscopic speed resemble a normal distribution with a mean of 1.38 m/second and standard deviation of 0.37 m/second. The acceleration distribution also bear a resemblance to the normal distribution with an average of 0.68 m/ square second. A physical based microscopic pedestrian simulation model was also developed. Both Microscopic Video Data Collection and Microscopic Pedestrian Simulation Model generate a database called NTXY database. The formulations of…
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Taxonomy
TopicsEvacuation and Crowd Dynamics · Traffic and Road Safety · Traffic control and management
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
