Stochastic Network Vehicular Origin-Destination Demand Using Multi-Sensor Information Fusion Approaches

The Introduction section of this report describes the problem of solving the heterogeneous sensors deployment problem (HSDP) and network O-D matrix estimation problem which is referred to as the HSDP-OD problem in this study. It addresses the HSDP-OD problem in an integrated manner using a two-stage optimization model where the error on the O-D matrix estimate in the second-stage model is fed back to modify the sensor deployment strategy in the first-stage model until some pre-specified error thresholds are met. The Methodology section characterizes the heterogeneous sensor based traffic information and presents the integrated model for the HSDP-OD problem, including the formulations of the heterogeneous sensors deployment and O-D matrix estimation models. It describes the solution procedure with the feedback mechanism to solve the integrated model. The Findings section discusses the results of numerical experiments based on real road network. Finally, concluding remarks are presented in the Summary and Recommendations section.

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

    Purdue University

    School of Civil Engineering, 550 Stadium Mall Drive
    West Lafeyette, IN  United States  47907

    NEXTRANS

    Purdue University
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  • Authors:
    • Liou, Han-Tsung
    • Hu, Shou-Ren
    • Peeta, Srinivas
    • Kim, Yong Hoon
    • Lee, Choungryeol
  • Publication Date: 2017-4-21

Language

  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Figures; References; Tables;
  • Pagination: 24p

Subject/Index Terms

Filing Info

  • Accession Number: 01646181
  • Record Type: Publication
  • Report/Paper Numbers: NEXTRANS Project No. 158PUY2.2
  • Contract Numbers: DTRT12-G-UTC05
  • Files: UTC, TRIS, RITA, ATRI, USDOT
  • Created Date: Sep 8 2017 7:46AM