Estimation of Time-Dependent Intersection Turning Proportions for Adaptive Traffic Signal Control under Limited Link Traffic Counts from Heterogeneous Sensors

Theoretically, an adaptive traffic signal control (ATSC) logic is superior to a pre-time or an actuated traffic signal control logic, because it can instantly respond to traffic dynamics to provide the respective signal control strategies by on-line algorithmic computations of desirable timing plans in order to reduce travel delays and/or queue lengths. Most existing ATSC systems require observed traffic link flows from densely installed sensors to capture dynamic vehicular evolutions, and some of them assume fixed intersection turning proportions, which is not realistic from a practical application’s perspective. To resolve these problems, this study solves the intersection turning proportions estimation problem by a Nonlinear Least Squares (NLS) model by taking advantage of heterogeneous sensor information in terms of partial link flow counts via vehicle detectors (VDs) and turning flow observations by license plate recognition (LPR) sensors. In addition, this study also seeks to address the optimal heterogeneous sensor deployment problem that maximizes traffic observability at urban intersections for a robust ATSC system. Finally, this study proposes an integrated ATSC system by incorporating traffic flow estimation and prediction using limited traffic information provided by different types of traffic sensors. The proposed ATSC logic is developed based on the COMDYCS-3E framework (Wu and Ho, 2009) which enhances its traffic flow estimation module and incorporates the sensor location model into the data input module.

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


    Purdue University
    3000 Kent Avenue
    Lafayette, IN  United States  47906-1075

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Authors:
    • Liou, Han-Tsung
    • Hu, Shou-Ren
    • Peeta, Srinivas
  • Publication Date: 2017-2-12


  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Figures; Maps; References; Tables;
  • Pagination: 18p

Subject/Index Terms

Filing Info

  • Accession Number: 01646076
  • Record Type: Publication
  • Report/Paper Numbers: NEXTRANS Project No. 110PUY2.1
  • Contract Numbers: DTRT12-G-UTC05
  • Created Date: Sep 8 2017 7:42AM