engleski

Computer vision and intelligent systems in road traffic control

Intelligent traffic control systems tackle today’s most significant problems in road transport, i.e. periodical road congestions. To ensure minimal losses related to congestion and optimal use of existing road infrastructure new approaches from the domain of intelligent transport systems (ITS) are applied. Today’s road traffic problems emphasis the need of cooperation between more standalone systems to achieve desired optimal use of the existing infrastructure. Development of such intelligent cooperative control systems presents an open challenge today. In order to implement such approaches, reliable measurements of traffic parameters and appropriate control algorithms are required. Trend in today’s traffic control systems is an broad increased use of cameras as the main sensor. From the video footage of traffic surveillance cameras several traffic parameters can be estimated like flow, vehicle gap and type, traffic speed, origin-destination matrices, etc. In this paper new approaches to road traffic control based on intelligent methods and computer vision proposed by the authors are described and newest acquired results are presented. For testing of the system real road traffic video footage was used from Croatian highways. Use case for testing of the proposed ramp metering framework was bypass of the city of Zagreb, Croatia. Section between problematic nodes with many on- and off-ramps was simulated in an augmented version of the macroscopic simulator CTMSIM.

Computer vision ; moving object detection ; trajectory estimation ; Kalman filter ; intelligent cooperative ramp metering ; ANFIS ; variable speed limit control ; intelligent transport systems (ITS)

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