Quantifying Traveler Information Provision in Dynamic Multiclass Traffic Networks

Information is effectively the same as a change in uncertainty, and therefore, they share the same unit system of measurement, such as bit, nat, and qubit. This paper adopts a strict definition of information and implements a method to quantify traveler information provision using an information-based modeling framework developed in earlier research. The framework combines a cognitive grouping model and information update scheme (learning) for calculating in quantified units the amount of information any traveler has about a route, which can be further decomposed to any sub-route during any time period of relevance. Such numerical quantification can be meaningful in evaluating network performance enhancement schemes such as ATIS and in modeling decision making when uncertainty is a significant factor. An application study with traffic network and detector data near downtown Los Angeles is used to demonstrated the use of the method for quantifying information provision from a dynamic message board, as an illustrative case. Further improvement and research directions are identified.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB20 Standing Committee on Effects of Information and Communication Technologies (ICT) on Travel Choices.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Yu, Jiangbo
    • Jayakrishnan, R
  • Conference:
  • Date: 2016

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 18p
  • Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01594292
  • Record Type: Publication
  • Report/Paper Numbers: 16-6101
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 21 2016 4:47PM