Testing the Importance of Fixing Exogenously Some Parameters in Aggregate Modal Split Models, by means of Sensitivity Analysis.

Abstract

Aggregate modal split (and distribution) models currently need exogenously determined values for such key parameters as the value of in-vehicle time, the value of waiting time and the car occupancy factor. Using hierarchical logit modal split models and data from the Garforth Corridor, to the east of Leeds, this paper set out to investigate the effects in the model aggrement to the data (and hence in its forecasting capabilities) of inputting different values for these parameters. 'To gain insight into the relative importance of each of these fixed parameters,the analytical point elasticities of the free parameters in the model with respect to them, were briefly examined. This exercise, together with some more practical post-hoc considerations led us to concentrate on the values of in-vehicle time and waiting time only. The rather surprising outcome of the analysis was that the model fits were not statistically different, for different values of the fixed parameters, their variation being accommodated by changes in the values of the free parameters. The main conclusion was that provided the exogeneous parameters are reasonably accurate they should produce models that are capable of performing as well (or badly) as models calibrated entirely from the data, and at a much lower cost