CVCYSep 7, 2016

Tracking Algorithm for Microscopic Flow Data Collection

arXiv:1609.02137v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses the need for automated data collection in traffic analysis, but it is incremental as it builds on existing tracking methods for fewer individuals.

The paper tackles the problem of tracking many individual vehicles or pedestrians for microscopic traffic flow data collection, resulting in a new and fast algorithm.

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

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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