Tracking Algorithm for Microscopic Flow Data Collection

TL;DR

This paper introduces a novel, fast tracking algorithm capable of simultaneously monitoring numerous pedestrians or vehicles, advancing microscopic traffic data collection methods beyond existing single or dual-object tracking approaches.

Contribution

The paper presents a new tracking algorithm that efficiently tracks many individuals simultaneously, filling a gap in microscopic traffic data collection research.

Findings

Successfully tracks multiple pedestrians and vehicles at once

Faster than existing tracking algorithms

Improves microscopic traffic data accuracy

Abstract

Various methods to automate traffic data collection have recently been developed by many researchers. A macroscopic data collection through image processing has been proposed. For microscopic traffic flow data, such as individual speed and time or distance headway, tracking of individual movement is needed. The tracking algorithms for pedestrian or vehicle have been developed to trace the movement of one or two pedestrians based on sign pattern, and feature detection. No research has been done to track many pedestrians or vehicles at once. This paper describes a new and fast algorithm to track the movement of many individual vehicles or pedestrians