Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89720
Title: Traffic state estimation using floating car data
Authors: Sunderrajan, Abhinav
Viswanathan, Vaisagh
Cai, Wentong
Knoll, Alois
Keywords: DRNTU::Engineering::Computer science and engineering
Traffic State Estimation
Simulation And Modelling Of Transportation Systems
Issue Date: 2016
Source: Sunderrajan, A., Viswanathan, V., Cai, W., & Knoll, A. (2016). Traffic state estimation using floating car data. Procedia Computer Science, 80, 2008-2018. doi:10.1016/j.procs.2016.05.521
Series/Report no.: Procedia Computer Science
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.
URI: https://hdl.handle.net/10356/89720
http://hdl.handle.net/10220/47120
ISSN: 1877-0509
DOI: 10.1016/j.procs.2016.05.521
Rights: © 2016 The Author(s). Published by Elsevier B. V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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