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

1. 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