Real time traffic models, decision support for traffic management

Luc Wismansa, Erik de Romph, Klaas Friso, Kobus Zantema

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various control strategies and enhance the performance of the overall network. By taking
proactive action deploying traffic management measures, congestion may be prevented or its effects limited. An approach of short-term traffic state prediction is presented and implemented in a real life case for the city of Assen in the Netherlands. This prediction is based on connecting online traffic measurements with a real time traffic model using the macroscopic dynamic
traffic assignment model StreamLine in a rolling horizon implementation. Different monitoring data sources consisting of both fixed-point and floating car data are used. The advantage of the rolling horizon approach is that no warming-up period is needed for the dynamic traffic assignment taking less computation time while keeping results consistent. Further, the current traffic state
estimation is done by combining model estimates of previous predictions and current measurements. The results of predictions made in the real life case are presented as well as several tested methods for improving the current state estimations showing promising results.
Original languageEnglish
Title of host publication12th International Conference on Design and Decision Support Systems in Architecture and Urban
Pages220-235
Number of pages16
Volume22
DOIs
Publication statusPublished - 2014
Event12th International Conference on Design and Decision Support Systems in Architecture and Urban Planning, DDSS 2014 - Eindhoven, Netherlands
Duration: 27 Aug 201229 Aug 2012

Publication series

NameProcedia Environmental Sciences
PublisherElsevier BV
Volume22
ISSN (Print)1878-0296

Conference

Conference12th International Conference on Design and Decision Support Systems in Architecture and Urban Planning, DDSS 2014
CountryNetherlands
CityEindhoven
Period27/08/1229/08/12

Keywords

  • Real time traffic models
  • traffic management
  • Sensor City Assen
  • dynamic traffic assignment
  • rolling horizon
  • state estimation

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