A fuzzy track-to-track association algorithm with dynamic time warping for trajectory-level vehicle detection

Siqi Wan, Huaqiao Mu, Ke Han, Taesu Cheong, Chi Xie

Research output: Contribution to journalArticlepeer-review

Abstract

Multi-source track-to-track association (TTTA), which identifies trajectories from multiple sensors or data sources of the same dynamic vehicle, is an important data fusion technique widely applied to vehicle detection in the fields of road, marine, and aviation transportation. However, issues such as time asynchrony, heterogeneous sampling intervals, and random sensing errors have posed considerable challenges to the accuracy and robustness of TTTA. Aiming to address these issues in an integrated manner, this paper proposes a TTTA algorithm that comprehensively calculates the similarity between trajectories using multiple trajectory features through dynamic time warping and Cauchy distribution degree of membership function. Multiple experimental datasets were generated by randomly sampling real AIS trajectory data into two trajectory data sources and adding random errors. The average association accuracy of all scenarios and error levels of the proposed method reached 97.33%, far higher than other benchmark methods. Experimental results demonstrated the advantage of the proposed algorithm in various TTTA scenarios, especially its robustness in intricate trajectory situations. The results also indicated that more features can maintain the stability of associations in the presence of larger random errors, and dynamic time warping can improve association accuracy in intricate scenarios. This study provides a practical solution for the problem of time asynchrony, heterogeneous sampling intervals, and random errors in multi-source trajectory data fusion, showcasing promising applications across diverse domains.

Original languageEnglish
JournalInternational Journal of Transportation Science and Technology
DOIs
Publication statusAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
© 2024 Tongji University and Tongji University Press

Keywords

  • Asynchronous trajectories
  • Degree of membership
  • Dynamic time warping
  • Track-to-track association
  • Vehicle detection

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Management, Monitoring, Policy and Law

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