A method for using crowd-sourced trajectories to construct control-independent fundamental diagrams at signalized links

This work presents a methodology for measuring traffic quantities from crowd-sourced trajectories for the purpose of estimating saturation flow rates. First, the observed trajectories are clustered to identify the signal programs that occur over the data collection period. Trajectories with known cycle lengths are accumulated on one space–time plot with their respective green start times at the origin, and then Edie’s generalized definitions of traffic variables are adapted to construct a full-scale fundamental diagram. The approach is tested empirically, and the averages and variances of the estimated quantities were within the expected ranges for each type of movement. Results from several movements were also verified against field measurements from a short video recording. The proposed method enables estimations of saturation flow rates over entire networks based on long-term datasets, instead of short-term field measurements. The approach is particularly advantageous for estimations under the unpredictable conditions associated with conflicting movements.

• Record URL:
  https://doi.org/10.1016/j.trc.2021.103270
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X21002825
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2021 Walid Fourati and Bernhard Friedrich. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Fourati, Walid
  • Friedrich, Bernhard
• Publication Date: 2021-9

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: 103270
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 130
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Crowdsourcing; Floating car data; Macroscopic traffic flow; Saturation flow; Signalized intersections; Trajectory; Urban areas
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01782745
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 24 2021 10:20AM