Traffic measurement and congestion detection based on real-time highway video data

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

1 Zitat (Scopus)

Abstract

Since global road traffic is steadily increasing, the need for intelligent traffic management and observation systems is becoming an important and critical aspect of modern traffic analysis. In this paper, we cover the development and evaluation of a traffic measurement system for tracking, counting and classifying different vehicle types based on real-time input data from ordinary highway cameras by using a hybrid approach including computer vision and machine learning techniques. Moreover, due to the relatively low framerate of such cameras, we also present a prediction model to estimate driving paths based on previous detections. We evaluate the proposed system with respect to different real-life road situations including highway-, toll station-and bridge-cameras and manage to keep the error rate of lost vehicles under 10%.

OriginalspracheEnglisch
Aufsatznummer6270
FachzeitschriftApplied Sciences (Switzerland)
Jahrgang10
Ausgabenummer18
DOIs
PublikationsstatusVeröffentlicht - Sep 2020

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