Published: February 2012 | Category: Transport demand management , Research programme , Research & reports | Audience: General
Generalised linear models (GLMs) provide a flexible and sound basis for calibrating gravity models for trip distribution, for a wide range of deterrence functions (from steps to splines), with K factors and geographic segmentation. The Tanner function fitted Wellington Transport Strategy Model data as well as more complex functions and was insensitive to the formulation of intrazonal and external costs. Weighting from variable expansion factors and interpretation of the deviance under sparsity are addressed.
An observed trip matrix was disaggregated and fitted at the household, person and trip levels with consistent results. Hierarchical GLMs (HGLMs) were formulated to fit mixed logit models, but were unable to reproduce the coefficients of simple nested logit models. Geospatial analysis by HGLM showed no evidence of spatial error patterns, either as random K factors or as correlations between them.
Trip distribution was calibrated from aggregate data by the MVESTM matrix estimation package, incorporating period and direction factors in the intercepts. Counts across four screenlines showed a significance similar to a thousand-household travel survey. Calibration was possible only in conjuction with trip end data. Criteria for validation against screenline counts were met, but only if allowance was made for error in the trip end data.
Errata
29 May 2013
Page 41, paragraph 6, sentence 2:
sentence corrected to read '…probability of choosing a destination is proportional…'
Page 109, table 4.10:
figures corrected
Page 369, paragraph 3, sentence 1:
sentence corrected to read '…having the same attraction meshblock…'
2 July 2013
Page 150, figures 4.28 and 4.29:
headings corrected to read 'Central Radial Regional'
Page 386, figure D.7:
title corrected to read 'Regional scheme users'
Page 386, figure D.8:
title corrected to read 'Regional scheme changes in traffic flows'
Keywords: calibration, deterrence function, deviance, geospatial, gravity, hierarchical generalised linear model, matrix estimation, mixed logit, MVESTM, regression, sparsity, transport model, trip distribution
