An Information-Based Framework for Incorporating Uncertainty in Transportation Modeling

This paper proposes a parsimonious modeling framework aimed at systematically incorporating perceived uncertainty into decision making. The model integrates theoretically sound concepts from information theory, communication, and cognitive science, in order to demystify concepts on information and uncertainty in existing research and practice. Difference between uncertainty and reliability are identified. Most existing modeling methods can be shown as special cases with certain assumptions on information availability and observer’s characteristics of perception which used to be implicit or unspecified. Potential applications are identified in information/uncertainty quantification, value-of-uncertainty (VOU) estimation, traffic assignment, simulation, departure time choice, ABM-DTA integration, system evaluation, etc.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Yu, Jiangbo
  • Jayakrishnan, R
• Conference:
  • Transportation Research Board 95th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2016-1-10 to 2016-1-14
• Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 20p
• Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Cognition; Decision making; Departure time; Reliability; Simulation; Traffic assignment; Travel time; Uncertainty
• Subject Areas: Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01593556
• Record Type: Publication
• Report/Paper Numbers: 16-4260
• Files: TRIS, TRB, ATRI
• Created Date: Mar 15 2016 10:07AM