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Published in: International Journal of Intelligent Transportation Systems Research 3/2021

16-07-2021

Exploring the Performance of Streaming-Data-Driven Traffic State Estimation Method Using Complete Trajectory Data

Authors: Garima Dahiya, Yasuo Asakura

Published in: International Journal of Intelligent Transportation Systems Research | Issue 3/2021

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Abstract

This study aims to evaluate the performance of an extended floating car data (xFCD)-based traffic state estimation method proposed by Seo et al. (2015), which does not rely on any strong assumptions such as Fundamental Diagram, using high-resolution complete trajectory data, viz. Zen Traffic Data (ZTD). Traffic state estimated by this method, considering randomly sampled trajectories of ZTD as those of probe vehicles with known penetration rates, are compared with ones obtained by complete ZTD by applying Edie’s generalized definitions. The variation in estimation errors and covering percentages are analyzed for varying settings: spatiotemporal resolution and probe penetration rates.

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Metadata
Title
Exploring the Performance of Streaming-Data-Driven Traffic State Estimation Method Using Complete Trajectory Data
Authors
Garima Dahiya
Yasuo Asakura
Publication date
16-07-2021
Publisher
Springer US
Published in
International Journal of Intelligent Transportation Systems Research / Issue 3/2021
Print ISSN: 1348-8503
Electronic ISSN: 1868-8659
DOI
https://doi.org/10.1007/s13177-021-00263-4

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