101-0491-00L  Agent Based Modeling in Transportation

SemesterAutumn Semester 2021
LecturersM. Balac
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
101-0491-00 GAgent Based Modeling in Transportation4 hrs
Mon09:45-11:30HPK D 24.2 »
Tue13:45-15:30HPK D 24.2 »
M. Balac

Catalogue data

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 in terms of which lectures the students should have previously attended. However, knowledge of basic statistical theory is expected, and experience with at least one high-level programming language (Java, R, Python, or other) is recommended.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits6 credits
ExaminersM. Balac
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition possible without re-enrolling for the course unit.

Learning materials

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Only public learning materials are listed.

Groups

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Restrictions

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Offered in

ProgrammeSectionType
Civil Engineering MasterDigitalisation Specific CoursesWInformation
Civil Engineering MasterMajor in Transport SystemsWInformation
Data Science MasterInterdisciplinary ElectivesWInformation
Spatial Development and Infrastructure Systems MasterMajor in Transport Systems and BehaviourWInformation
Spatial Development and Infrastructure Systems MasterMajor in Transport Systems and BehaviourWInformation
Environmental Sciences MasterModeling and Statistical AnalysisWInformation