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Malfunction Sniffing – A New Approach for On-Site Quality Evaluations of Traffic Data Acquisition Infrastructure

Carsten Kühnel, Toni Weisheit, Robert Hoyer

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Abstract

In recent years, many efforts have been made to improve traffic flow and to reduce traffic problems based on traffic detections. In order to achieve it, methods to influence the traffic are necessary (e.g. traffic actuated signal control, network control). The success of these methods depends on the correctness of underlying traffic data. As a part of the German research project TRAFFIC IQ procedures for verifying the quality of traffic data and traffic data collection systems are being developed. The Malfunction Sniffer, a tool to carry out on-site quality checks of detection infrastructure was designed in order to support the development of any quality analyzing algorithms. The Malfunction Sniffer was developed and prototypically implemented by the Department of Traffic Engineering and Transport Logistics of the University of Kassel in cooperation with the City of Dusseldorf. With its help, detectors can be checked on their detection accuracy. After an initial on-site search for defective detectors, long time monitorings on the identified detectors are conducted.

About this research paper

What this paper is about

In recent years, many efforts have been made to improve traffic flow and to reduce traffic problems based on traffic detections. In order to achieve it, methods to influence the traffic are necessary (e.g. traffic actuated signal control, network control). The success of these methods depends on the correctness of underlying traffic data. As a part of the German research project TRAFFIC IQ procedures for verifying the quality of traffic data and traffic data collection systems are being developed. The Malfunction Sniffer, a tool to carry out on-site quality checks of detection infrastructure was designed in order to support the development of any quality analyzing algorithms. The Malfunction Sniffer was developed and prototypically implemented by the Department of Traffic Engineering and Transport Logistics of the University of Kassel in cooperation with the City of Dusseldorf. With its help, detectors can be checked on their detection accuracy. After an initial on-site search for defective detectors, long time monitorings on the identified detectors are conducted.

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Available abstract

In recent years, many efforts have been made to improve traffic flow and to reduce traffic problems based on traffic detections. In order to achieve it, methods to influence the traffic are necessary (e.g. traffic actuated signal control, network control). The success of these methods depends on the correctness of underlying traffic data. As a part of the German research project TRAFFIC IQ procedures for verifying the quality of traffic data and traffic data collection systems are being developed. The Malfunction Sniffer, a tool to carry out on-site quality checks of detection infrastructure was designed in order to support the development of any quality analyzing algorithms. The Malfunction Sniffer was developed and prototypically implemented by the Department of Traffic Engineering and Transport Logistics of the University of Kassel in cooperation with the City of Dusseldorf. With its help, detectors can be checked on their detection accuracy. After an initial on-site search for defective detectors, long time monitorings on the identified detectors are conducted.

Key concepts: Computer science, Correctness, Quality (philosophy), Data quality, Data collection, Traffic flow (computer networking), Control (management), Detector

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