101-0491-00L  Agent Based Modeling in Transportation

SemesterAutumn Semester 2022
LecturersM. Balac
Periodicityyearly recurring course
Language of instructionEnglish


AbstractThis course provides an introduction to agent-based modeling in transportation. The lectures and exercises offer an opportunity to learn about agent-based models' current methodology, focusing on MATSim, how agent-based models are set up, and perform a practical case study by working in teams.
ObjectiveAt the end of the course, the students should:
- have an understanding of agent-based modeling
- have an understanding of MATSim
- have an understanding of the process needed to set up an agent-based study
- have practical experience of using MATSim to perform practical transportation studies
ContentThis course provides an introduction to agent-based models for transportation policy analysis. Four essential topics are covered:

1) Introduction of agent-based modeling and its comparison to the traditional state of practice modeling
2) Introduction of MATSim, an open-source agent-based model, developed at ETH Zurich and TU Berlin, and its various parts
3) Setting up an agent-based model simulation, where different statistical methods used in the process will be introduced and explained. Here the open-source eqasim framework used at ETH Zurich to set up agent-based models will be introduced
4) Conducting a transport policy study. The case study will be performed in groups and will include a paper-like report.

During the course, outside lecturers will give several lectures on using MATSim in practice (i.e., SBB).
LiteratureAgent-based modeling in general
Bonabeau, E. (2002). Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the national academy of sciences, 99(suppl 3), 7280-7287.
Helbing, D (2012) Social Self-Organization, Understanding Complex Systems, Springer, Berlin.
Heppenstall, A., A. T. Crooks, L. M. See and M. Batty (2012) Agent-Based Models of Geographical Systems, Springer, Dordrecht.

MATSim

Horni, A., K. Nagel and K.W. Axhausen (eds.) (2016) The Multi-Agent Transport Simulation MATSim, Ubiquity, London
(Link)

Additional relevant readings, primarily scientific articles, will be recommended throughout the course.
Prerequisites / NoticeThere are no strict preconditions regarding which lectures the students should have previously attended. However, experience with at least one high-level programming language (Java, R, Python, or other) is recommended.

Crash course 101-0491-10 Basics of Java and Best Practices for Scientific Computing before the start of HS is recommended.