Vehicle Trajectory Reconstruction and Home Places Estimation from Monitoring Data

Analyzing vehicle travel information and roadway network traffic state of perception data has been a popular research topic. In order to excavate the vehicle travel characteristics in the city of Rui’an from monitoring data, the authors proposed a trajectory reconstruction model integrated into the ordered weighted averaging (OWA) and setting four attributes to solve trajectory records missing phenomenon, the authors verified the model’s reliability through actual experiments. Then they devised a method combining two algorithms to estimate the important places of each individual vehicle based on the reconstructed vehicles trajectory. The authors' results showed that the method using the K-means algorithm makes good predictions: 97% of the distances between the actual places and estimated places are within 2 km. Both the trajectory reconstruction and home places estimation will provide data support for studying vehicle commuting and road network characteristics.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 2203-2212
  • Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility

Subject/Index Terms

Filing Info

  • Accession Number: 01874430
  • Record Type: Publication
  • ISBN: 9780784481523
  • Files: TRIS, ASCE
  • Created Date: Feb 23 2023 1:15PM