Travel Time Estimation of a Single Segment Based on Freeway Toll Data

Travel time is one of the most important indexes to describe freeway traffic conditions, and the spatial and temporal variation of traffic conditions can support operational decision-making for administrators and trip-planning for travelers. The closed toll system of the freeway in China contains a large amount of travel information (e.g., vehicle type, entry/exit station, and entry/exit time), and the toll data can be used to estimate the route travel time directly (i.e., exit time minus entry time). Compared to the route travel time, single segment (i.e. the mainline between two adjacent toll stations) travel time represents the spatial variation of traffic conditions more accurately. With a short time interval (e.g. 15 minutes), single segment travel time is also good at describing the temporal variation of traffic conditions. However, single segment travel time estimation is always unreliable when only using the adjacent toll stations' data due to the insufficient data with finer resolution. This study proposed a method to solve this problem by using toll information from all vehicles that pass through the single segment. A case study on the Huning Freeway, which is the busiest freeway in Jiangsu province, is used to validate the method. A total of 74,684 toll data records in four hours was used after quality control and data filtering. The results demonstrated the spatial and temporal variation of traffic conditions in 15-minute time intervals for the 274-km-long freeway, and the location and duration of congestion were precisely identified. Biased estimation results are discussed and improvement is proposed. The method will contribute to a better understanding of freeway traffic condition variations without additional monitoring facilities.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 2161-2174
  • Monograph Title: CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems

Subject/Index Terms

Filing Info

  • Accession Number: 01531821
  • Record Type: Publication
  • ISBN: 9780784413623
  • Files: TRIS, ASCE
  • Created Date: Jul 2 2014 3:03PM