Trip table realization underlying stochasticity and its effects on assigned link flows
This presentation is the property of its rightful owner.
Sponsored Links
1 / 1

Trip Table Realization: Underlying Stochasticity and Its Effects on Assigned Link Flows PowerPoint PPT Presentation


  • 80 Views
  • Uploaded on
  • Presentation posted in: General

Trip Table Realization: Underlying Stochasticity and Its Effects on Assigned Link Flows . Wenjing Pu (PhD student), David Boyce, PhD, Jie (Jane) Lin, PhD Department of Civil and Materials Engineering & Institute of Environmental Science and Policy

Download Presentation

Trip Table Realization: Underlying Stochasticity and Its Effects on Assigned Link Flows

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Trip table realization underlying stochasticity and its effects on assigned link flows

Trip Table Realization: Underlying Stochasticity and Its Effects on Assigned Link Flows

WenjingPu (PhD student), David Boyce, PhD, Jie (Jane) Lin, PhD

Department of Civil and Materials Engineering & Institute of Environmental Science and Policy

Department of Civil and Environmental Engineering, Northwestern University

  • A static trip table can only represent the travel demand distribution during a specific time period (e.g. peak hours) of a day

  • Random day-to-day variations in travel demand, however, inherently exist

  • This research aims to explore the impacts of trip table random day-to-day variation on assigned link flows and costs

  • The original static trip table is assumed to be the “mean” trip table for the modeling period (e.g. peak hours) over a number of days

  • Each O-D demand (cell value) is independent and has a Poisson distribution about the original value

  • Inverse transformation was used to generate random number of trips for each OD pair

  • Total 30 realized trip tables were simulated for Chicago and Barcelona network, respectively

  • All original and realized trip tables were assigned to relevant networks using command code TAPAS

  • Although large discrepancy exists for the cell-level OD trips, the overall variability of the assigned link flows and costs is fairly small

  • Justified the common practice of only using only one original trip table to do trip assignment when the objective is to obtain overall network performance measurements, such as VMT, VHT

  • However, it should be cautioned in drawing conclusions on a sub-network level analysis (individual link level) and scenario analysis where large link flow variations may be found

  • Future research could relax the Poisson assumption


  • Login