Data-Driven Freeway Performance Evaluation Framework for Project Prioritization and Decision Making

This report describes methods that potentially can be incorporated into the performance monitoring and planning processes for freeway performance evaluation and decision making. Reliability analysis was conducted on the selected I-15 corridor by employing congestion frequency as the performance measure. Hot spots during peak hours were identified through sensitivity analysis. A data-driven algorithm combining spatiotemporal analysis and shockwave theory was developed to determine secondary incidents. Incident-induced delay was further quantified through spatiotemporal pattern recognition. The average delay induced by incidents aligns well with the incidents’ severity and impact. Several hot spots suffered from higher delays and were explored in further detail. A statistical mechanism was developed to determine adverse weather impact on travel. Using the weather records in 2013 and mapping with the PeMS traffic database, volume and delay were estimated under normal conditions and compared with adverse weather conditions. The analysis of different roadway conditions reveals that the general parabolic pattern of speed and volume disappear under severe adverse weather condition. The mechanism was able to identify the causes for reduced volume under a variety of scenarios through empirical data, either due to roadway capacity reduction or travel demand reduction.

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  • Supplemental Notes:
    • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
  • Corporate Authors:

    University of Utah, Salt Lake City

    Department of Civil and Environmental Engineering
    122 South Central Campus Drive
    Salt Lake City, UT  United States  84112

    Mountain-Plains Consortium

    North Dakota State University
    Fargo, ND  United States  58108

    Utah Department of Transportation

    4501 South 2700 West
    Salt Lake City, UT  United States  84114-8410

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Authors:
    • Liu, Xiaoyue Cathy
    • Chen, Zhuo
  • Publication Date: 2017-1


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 46p

Subject/Index Terms

Filing Info

  • Accession Number: 01630055
  • Record Type: Publication
  • Created Date: Mar 27 2017 9:29AM