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A probabilistic framework for traffic data quality

Ebendt, Rüdiger and Neumann, Thorsten (2018) A probabilistic framework for traffic data quality. Transport Research Arena 2018, 16.-19. April 2018, Wien, Österreich. DOI: 10.5281/zenodo.1440850

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Official URL: https://doi.org/10.5281/zenodo.1440850

Abstract

Regarding the assessment of traffic data in ITS, there is an increasing need for answers to the following questions: (i) What exactly is "traffic data quality"?, and, related to that, (ii) There are too many ways to define and to do things, and results of different researchers are inconsistent or not comparable. How can we overcome this situation? With that background, an important aim of the ongoing DLR-project I.MoVe is to develop a consistent understanding of traffic data quality, together with a unified framework for its assessment. To this end, a probabilistic framework for traffic data quality is provided in this paper. Real-world examples from I.MoVe demonstrate its application for the assessment of data sources like induction loops, stationary bluetooth sensors and floating car data (FCD). A first important point is to distinguish strictly between quality indices, quality requirements, and quality itself. While the present framework develops quality indices based on established quality criteria like accuracy, completeness, validity, and coverage, the usual understanding of quality is extended to a probabilistic view. This also addresses the problem of information retrieval in the presence of vagueness and uncertainty. The provided examples are making full use of the proposed framework, and also constitute interesting results for the practitioner by themselves. Examples include the assessment of induction loop count data, and assessing the temporal coverage of a stretch of road with stationary bluetooth data, or of the whole city of Berlin, Germany with FCD.

Item URL in elib:https://elib.dlr.de/123895/
Document Type:Conference or Workshop Item (Speech)
Title:A probabilistic framework for traffic data quality
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ebendt, RüdigerRuediger.Ebendt (at) dlr.dehttps://orcid.org/0000-0002-3565-7024
Neumann, ThorstenThorsten.Neumann (at) dlr.dehttps://orcid.org/0000-0002-9236-0585
Date:2018
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.5281/zenodo.1440850
Page Range:pp. 1-10
Status:Published
Keywords:quality, traffic data quality, probability theory, probabilistic framework
Event Title:Transport Research Arena 2018
Event Location:Wien, Österreich
Event Type:international Conference
Event Dates:16.-19. April 2018
Organizer:Austrian Ministry for Transport, Innovation and Technology, AIT, Austriatech
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - I.MoVe (old)
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems
Deposited By: Ebendt, Dr.rer.nat. Rüdiger
Deposited On:11 Dec 2018 12:57
Last Modified:10 Jul 2019 11:03

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