research-article

A data stream-based evaluation framework for traffic information systems

Authors:

Sandra Geisler,

Christoph Quix,

Stefan SchifferAuthors Info & Claims

IWGS '10: Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming

Pages 11 - 18

https://doi.org/10.1145/1878500.1878505

Published: 02 November 2010 Publication History

Abstract

Traffic information systems based on mobile, in-car sensor technology are a challenge for data management systems as a huge amount of data has to be processed in real-time. Data mining methods must be adapted to cope with these challenges in handling streaming data. Although several data stream mining methods have been proposed, an evaluation of such methods in the context of traffic applications is yet missing. In this paper, we present an evaluation framework for data stream mining for traffic applications. We apply a traffic simulation software to emulate the generation of traffic data by mobile probes. The framework is evaluated in a first case study, namely queue-end detection. We show first results of the evaluation of a data stream mining method, varying multiple parameters for the traffic simulation. The goal of our work is to identify parameter settings for which the data stream mining methods produce useful results for the traffic application at hand.

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Cited By

Kargupta HKargupta P(2019)Analyzing Driving Data using the ADAPT Distributed Analytics Platform for Connected Vehicles2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA.2019.00074(590-599)Online publication date: Oct-2019
https://doi.org/10.1109/DSAA.2019.00074
Brandt TGrawunder M(2018)GeoStreamsACM Computing Surveys10.1145/317784851:3(1-37)Online publication date: 23-May-2018
https://dl.acm.org/doi/10.1145/3177848
Tran DGaber MSattler K(2014)Change detection in streaming data in the era of big dataACM SIGKDD Explorations Newsletter10.1145/2674026.267403116:1(30-38)Online publication date: 25-Sep-2014
https://dl.acm.org/doi/10.1145/2674026.2674031
Show More Cited By

Index Terms

A data stream-based evaluation framework for traffic information systems
1. Information systems
  1. Information retrieval
    1. Evaluation of retrieval results

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cover image ACM Conferences

IWGS '10: Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming

November 2010

67 pages

ISBN:9781450304313

DOI:10.1145/1878500

Editors:
Mohamed Ali
Microsoft
,
Erik Hoel
ESRI
,
Cyrus Shahabi
University of Southern California

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 November 2010

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Bundesministerium für Bildung und Forschung

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GIS '10

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SIGSPATIAL

GIS '10: 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2, 2010

California, San Jose

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Overall Acceptance Rate 7 of 9 submissions, 78%

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Cited By

Kargupta HKargupta P(2019)Analyzing Driving Data using the ADAPT Distributed Analytics Platform for Connected Vehicles2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA.2019.00074(590-599)Online publication date: Oct-2019
https://doi.org/10.1109/DSAA.2019.00074
Brandt TGrawunder M(2018)GeoStreamsACM Computing Surveys10.1145/317784851:3(1-37)Online publication date: 23-May-2018
https://dl.acm.org/doi/10.1145/3177848
Tran DGaber MSattler K(2014)Change detection in streaming data in the era of big dataACM SIGKDD Explorations Newsletter10.1145/2674026.267403116:1(30-38)Online publication date: 25-Sep-2014
https://dl.acm.org/doi/10.1145/2674026.2674031
Balkesen CTatbul NÖzsu MChakravarthy SUrban SPietzuch PRundensteiner E(2013)Adaptive input admission and management for parallel stream processingProceedings of the 7th ACM international conference on Distributed event-based systems10.1145/2488222.2488258(15-26)Online publication date: 29-Jun-2013
https://dl.acm.org/doi/10.1145/2488222.2488258
Imai HMaeda KChiba TNegishi YKoseki AAihara TKomatsu H(2013)An event-processing system alerting analytically to networked vehicles16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)10.1109/ITSC.2013.6728278(485-492)Online publication date: Oct-2013
https://doi.org/10.1109/ITSC.2013.6728278
Krogh BAndersen OTorp KAli MBanaei-Kashani FHoel E(2012)Trajectories for novel and detailed traffic informationProceedings of the 3rd ACM SIGSPATIAL International Workshop on GeoStreaming10.1145/2442968.2442973(32-39)Online publication date: 6-Nov-2012
https://dl.acm.org/doi/10.1145/2442968.2442973
Geisler SQuix CSchiffer SJarke M(2012)An evaluation framework for traffic information systems based on data streamsTransportation Research Part C: Emerging Technologies10.1016/j.trc.2011.08.00323(29-55)Online publication date: Aug-2012
https://doi.org/10.1016/j.trc.2011.08.003
Patroumpas KSellis T(2012)Event processing and real-time monitoring over streaming traffic dataProceedings of the 11th international conference on Web and Wireless Geographical Information Systems10.1007/978-3-642-29247-7_10(116-133)Online publication date: 12-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-29247-7_10

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