Traffic state estimation using floating car data

Abhinav Sunderrajan, Vaisagh Viswanathan, Wentong Cai, Alois Knoll

Research output: Contribution to journalConference articlepeer-review

27 Scopus citations

Abstract

There is an increasing availability of floating car data both historic, in the form of trajectory datasets and real-time, in the form of continuous data streams. This paves the way for several advanced traffic management services such as current traffic state estimation, congestion and incident detection and prediction of the short-term evolution of traffic flow. In this paper, we present an analysis of using probe vehicles for reconstructing traffic state. We employ detailed agent-based microscopic simulations of a real world expressway to estimate the state from floating car data. The probe penetration required for accurate traffic state estimation is also determined.

Original languageEnglish
Pages (from-to)2008-2018
Number of pages11
JournalProcedia Computer Science
Volume80
DOIs
StatePublished - 2016
EventInternational Conference on Computational Science, ICCS 2016 - San Diego, United States
Duration: 6 Jun 20168 Jun 2016

Keywords

  • Agent-based simulations
  • Simulation and modelling of transportation systems
  • Traffic state estimation

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