Efficiency Evaluation of Signal Control Intersections Based on Trajectory Data

The efficiency evaluation of a signal control intersection is the basis of signal optimization. Green time utilization is one of the most important evaluation indicators. In current studies, the most common input is traffic volume data from fixed detectors, which might not be accurate or available. This paper proposes a method using trajectory data instead. Based on the stop-wave and dissipation-wave information, three indicators were proposed to comprehensively evaluate the utilization of green time. A field case study was used to show the effectiveness, and a sensitivity analysis was carried out to illustrate the applicability. Results showed that when the penetration rate reaches 10% with a 2 h database or when the total sampling time reaches four hours under the penetration rate of 5%, the mean absolute percent error value of the overall green time utilization rate will be less than 10% and the performance will be relatively stable.

• Record URL:
  • https://doi.org/10.1061/9780784483053.026
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784483053
• Supplemental Notes:
  • © 2020 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Chen, Bei
  • Fu, Tao
  • Wang, Ling
  • Yu, Chunhui
  • Ma, Wanjing
• Conference:
  • 20th COTA International Conference of Transportation Professionals
  • Location: Xi’an , China
  • Date: 2020-8-14 to 2020-8-16
• Publication Date: 2020

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 302-314
• Monograph Title: CICTP 2020: Transportation Evolution Impacting Future Mobility

Subject/Index Terms

• TRT Terms: Green interval; Sensitivity analysis; Signalized intersections; Traffic data; Vehicle trajectories
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01767325
• Record Type: Publication
• ISBN: 9780784483053
• Files: TRIS, ASCE
• Created Date: Mar 22 2021 10:34AM