Modelling car availability, modal split and trip distribution by Monte-Carlo simulation: A short way to integrated models

Abstract

The model used a Monte-Carlo algorithm to simulate modal split and trip distribution as an interconnected decision process at the individual level. Using census data, the individuals of a planning region are classified into “situation groups”, which represent significantly different decision situations with respect to socio-demographic position and territorial location. According to the theoretical framework, which emphasises mobility constraints instead of preferences, household structure and sex (time budget and car availability constraints) and work place characteristics (location constraints) are the key variables. For each situation group, “decision profiles” are empirically determined; these describe car availability, travel time constraints and work place distribution. Modal split and trip distribution are simulated as an interconnected individual decision process, which is stochastically determined by the location of the individual and the decision profile of his situation group. The algorithm is very sensitive and flexible and extremely well suited to electronic processing. An extended and modified version is currently being used in the preparation of regional transporation plans for several German city regions.