MASS-GT

An empirical model for the simulation of freight policies

Journal Article (2025)
Author(s)

Michiel de Bok (Significance, TU Delft - Transport, Mobility and Logistics)

Lorant A. Tavasszy (TU Delft - Transport and Logistics, TU Delft - Transport, Mobility and Logistics)

Sebastiaan Thoen (Significance)

Larissa Eggers (Significance)

Ioanna Kourounioti (Panteia)

Research Group
Transport, Mobility and Logistics
DOI related publication
https://doi.org/10.1016/j.simpat.2025.103140
More Info
expand_more
Publication Year
2025
Language
English
Research Group
Transport, Mobility and Logistics
Volume number
142
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Despite the importance of urban freight transportation for the accessibility and livability of cities, few systematic, quantitative and empirical methods exist which allow an impact assessment of urban freight transportation solutions or policies. There is a lack of transparent literature on the full specification and estimation of these models, which not only hampers continued research, but also the development of evidence-based urban freight transport policies. We present the urban freight simulator Multi-Agent Simulation System for Goods Transport (MASS-GT) with its full specification and empirical implementation for a study area in The Netherlands. It concerns an agent-based model based on a framework of discrete choice and optimization models, which describes logistic choices of shippers, carriers, producers and consumers. The disaggregate level of detail allows the analysis of a wide variety of logistic developments and policies across all or specific logistic segments. The model is estimated and validated using a variety of data sources: truck trip diaries, supply/use statistics, an e-commerce demand survey, traffic counts and other relevant statistics. The article presents the full specifications of the model and their empirical estimation, including the data sources used. Also, the validity of the model is evaluated using road freight traffic counts. Finally, examples of applications of the model to case studies are provided.