Application of an empirical multi-agent model for urban goods transport to analyze impacts of zero emission zones in The Netherlands

Abstract

Reducing emissions caused by urban freight transportation is an increasingly important policy objective for transportation planners around the world. New and innovative ways of data collection provide new possibilities to analyze these issues. In this paper we present MASS-GT, a new multi-agent simulation system for urban goods transport. The empirical basis is provided by an exceptionally large dataset of truck trip travel diaries for The Netherlands that was collected from transportation management systems using an automated data collection interface. The dataset is very dense and includes information on vehicles, routes, and shipments carried. The strategic part of the model simulates the formation of individual shipments based on logistic processes at a strategic level, such as sourcing, distribution channel choice and shipment size choice. At tactical level disaggregate choices are simulated for tour formation, vehicle type- and time of day choice, based on observed distributions. The multi-agent approach allows to implement heterogeneous preferences and thus differentiated responses to new policies. We present an application of the model to study the impacts of urban consolidation centers (UCC) and zero emission zones. The freight transportation volumes transported to these UCC and their impact on logistic indicators are analyzed. Simulation results show that vehicle kilometers travelled within the wider region increase with the introduction of UCC, and at the same time the efficiency of deliveries increases as well. Thus the model allows to study trade-offs between regional and local systems that emerge from different behavioural responses to policies.