Reconstruction Method for Multi-Vehicle Trajectories on Arterials Driven by Multi-Source Data

Vehicle trajectories contain enriched spatial and temporal traffic information. In this study, the vehicle trajectory data were obtained after the data-fusion process of multi-source heterogeneous data on arterials. Both the piecewise cubic Hermite interpolation algorithm and cubic spline interpolation algorithm were used to reconstruct the single vehicle trajectories. A cross-validation method was applied in the comparison for obtaining the optimal model. Based on the reconstructed vehicle trajectories, an interpolation method was used to predict the unrecorded multi-vehicle trajectories by interpolating the time of unknown vehicles. The results show that the piecewise cubic Hermite interpolation can achieve better performance in reconstructing the single-vehicle trajectory and it is effective in predicting the missing trajectories. This study supports the spatial-temporal analysis of vehicle trajectories, traffic-state estimation, and transportation optimization.

• Record URL:
  • https://doi.org/10.1061/9780784484869.207
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784484869
• Supplemental Notes:
  • © 2023 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Zhao, Xin
  • Ren, Gang
  • Ma, Jingfeng
  • Wang, Shuyi
  • Deng, Yue
• Conference:
  • 23rd COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2023-7-14 to 2023-7-17
• Publication Date: 2023

Language

• English

Media Info

• Pagination: pp 2189-2198
• Monograph Title: CICTP 2023: Innovation-Empowered Technology for Sustainable, Intelligent, Decarbonized, and Connected Transportation

Subject/Index Terms

• TRT Terms: Arterial highways; Data fusion; Interpolation; Traffic data; Vehicle trajectories
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01906626
• Record Type: Publication
• ISBN: 9780784484869
• Files: TRIS, ASCE
• Created Date: Jan 31 2024 9:16AM