Abstract

Supernetworks have long been adopted to address multi-dimensional choice problems, which are thorny to solve for classic singular networks. Originated from combining transport mode and route choice into a multi-modal network, supernetworks have been extended into multi-state networks to include activity-travel scheduling, centered around activity-based models of travel demand. A key feature of the network extensions is that multiple choice facets pertaining to conducting a full activity program can be modeled in a consistent and integrative fashion. Thus, interdependencies and constraints between related choice facets can be readily captured. Given this advantage of integrity, the modeling of supernetwork has become an emerging topic in transportation research. This paper summarizes the recent progress in modeling multi-state supernetworks and discusses future prospects. Document type: Article

Abstract

Scenario describing the future include many disruptive innovations, which implies that traditional models calibrated on historical data are not always applicable for quantification of these scenarios. This paper describes disruptive changes to be expected which will influence the reliability of forecasting approaches used for road transport assessments and which changes to these approaches can be recommended. Also adaptions to the forecasting framework are proposed and the key modelling issues to be improved are indicated. Some aspects will remain hard to predict and in these cases additional pro-active mitigation actions are recommended, such as flexibilization of the infrastructure and location policy for economic activities.