An empirical agent-based simulation system for urban goods transport (MASS-GT)

Abstract

Urban planners face a few challenges in making urban freight transport more sustainable: reduce urban congestion, provide reliable delivery windows, decrease logistic costs, reduce emissions, improve safety. New data may provide a key in tackling these issues. This paper presents an agent-based urban freight modeling framework: MASS-GT. Objective of the project is to develop a comprehensive simulation framework that describes logistic decision making in the context of urban transport planning. Empirical basis is provided by a large dataset with observed freight transport data for The Netherlands. Part of the data has been collected using an automated procedure to report complete freight trip patterns from the transport management system. This provides more dense and complete data compared to conventional internet surveys. The paper describes the design principles for agents, markets and logistic decisions. Furthermore we elaborate on the incremental development path of building a comprehensive agent-based simulation system. We describe the first baseline prototype of the agent based modeling framework that simulates all urban freight transport patterns for an urban area, in the case the agglomeration of Rotterdam. This baseline model applies a data driven simulation approach; future work will consists of further improving this framework with the implementation of discrete choice models for logistic decisions.