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Traffic State Estimation in Congestion to Extend Applicability of DFOS

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arxiv 2508.21138 v1 pith:ZWRWMBLS submitted 2025-08-28 eess.SY cond-mat.stat-mechcs.SYnlin.CGphysics.soc-ph

Traffic State Estimation in Congestion to Extend Applicability of DFOS

classification eess.SY cond-mat.stat-mechcs.SYnlin.CGphysics.soc-ph
keywords dfosmeanapplicabilitycongestiondatamethodtraffictrajectories
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper presents a traffic state estimation (TSE) method in congestion for distributed fiber-optic sensing (DFOS). DFOS detects vehicle driving vibrations along the optical fiber and obtains their trajectories in the spatiotemporal plane. From these trajectories, DFOS provides mean velocities for real-time spatially continuous traffic monitoring without dead zones. However, when vehicle vibration intensities are insufficiently low due to slow speed, trajectories cannot be obtained, leading to missing values in mean velocity data. It restricts DFOS applicability in severe congestion. Therefore, this paper proposes a missing value imputation method based on data assimilation. Our proposed method is validated on two expressways in Japan with the reference data. The results show that the mean absolute error (MAE) of the imputed mean velocities to the reference increases only by 1.5 km/h as compared with the MAE of non-missing values. This study enhances the wide-range applicability of DFOS in practical cases.

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  1. Optimal-Control Suggestion for Congestion on Freeways using Data Assimilation of Distributed Fiber-Optic Sensing

    eess.SY 2026-04 unverdicted novelty 4.0

    Data assimilation of distributed fiber-optic sensing enables simulation-based optimal control of freeways, yielding 10-15% higher throughput and 20-30% higher mean speed when combining variable speed limits with inflo...