Capacity Models for Long-Term and Short-Term Freeway Work Zones in Germany

The paper presents results from a comprehensive study of work zone capacity on German freeways. A large number of long-time work zones with and without a reduction of the number of lanes as well as short-term work zones with temporary lane closures were included in the analysis. Data from loop or radar detectors upstream of the work zones were analyzed. For the capacity estimation of long-term work zones, both deterministic and stochastic methodologies were applied. It turned out that the methods for stochastic capacity analysis performed better than the conventional approach of estimating the capacity in the speed-flow diagram due to the short analysis periods covering work zone implementation. For short-term work zones, valid capacity estimates could only be determined for the post-breakdown queue discharge flow. The estimated capacities were analyzed regarding the influence of the prevailing traffic, geometric, and control conditions in the work zone. Relevant parameters are the number of lanes, the lane widths, the existence of divided lanes, the longitudinal gradient, the share of commuters, and the percentage of heavy vehicles. For short-time work zones, also the side of the lane closure (left or right lane) turned out to influence the capacity. As a result of the study, comprehensive capacity models for both long- and short-term work zones, which can be applied in work zone planning procedures, are provided.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AHB40 Standing Committee on Highway Capacity and Quality of Service.
  • Authors:
    • von der Heiden, Nina
    • Geistefeldt, Justin
  • Conference:
  • Date: 2018


  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 14p

Subject/Index Terms

Filing Info

  • Accession Number: 01663571
  • Record Type: Publication
  • Report/Paper Numbers: 18-00027
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 22 2018 11:57AM