101-0491-00L Agent Based Modeling in Transportation
Semester | Herbstsemester 2018 |
Dozierende | T. J. P. Dubernet, M. Balac |
Periodizität | jährlich wiederkehrende Veranstaltung |
Lehrsprache | Englisch |
Lehrveranstaltungen
Nummer | Titel | Umfang | Dozierende | |||||||
---|---|---|---|---|---|---|---|---|---|---|
101-0491-00 G | Agent Based Modeling in Transportation | 4 Std. |
| T. J. P. Dubernet, M. Balac |
Katalogdaten
Kurzbeschreibung | This lectures provides a round tour of agent based models for transportation policy analysis. First, it introduces statistical methods to combine heterogeneous data sources in a usable representation of the population. Then, agent based models are described in details, and applied in a case study. |
Lernziel | At the end of the course, the students should: - be aware of the various data sources available for mobility behavior analysis - be able to combine those data sources in a coherent representation of the transportation demand - understand what agent based models are, when they are useful, and when they are not - have working knowledge of the MATSim software, and be able to independently evaluate a transportation problem using it |
Inhalt | This lecture provides a complete introduction to agent based models for transportation policy analysis. Two important topics are covered: 1) Combination of heterogeneous data sources to produce a representation of the transport system At the center of agent based models and other transport analyses is the synthetic population, a statistically realistic representation of the population and their transport needs. This part will present the most common types of data sources and statistical methods to generate such a population. 2) Use of Agent-Based methods to evaluate transport policies The second part will introduce the agent based paradigm in details, including tradeoffs compared to state-of-practice methods. An important part of the grade will come from a policy analysis to carry with the MATSim open-source software, which is developed at ETH Zurich and TU Berlin and gets used more and more by practitioners, notably the Swiss rail operator SBB. |
Literatur | Agent-based modeling in general 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, mostly scientific articles, will be recommended throughout the course. |
Voraussetzungen / Besonderes | There 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 high-level programming languages (Java, R, Python...) is useful. |
Leistungskontrolle
Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
Leistungskontrolle als Semesterkurs | |
ECTS Kreditpunkte | 6 KP |
Prüfende | M. Balac, T. J. P. Dubernet |
Form | benotete Semesterleistung |
Prüfungssprache | Englisch |
Repetition | Repetition ohne erneute Belegung der Lerneinheit möglich. |
Lernmaterialien
Keine öffentlichen Lernmaterialien verfügbar. | |
Es werden nur die öffentlichen Lernmaterialien aufgeführt. |
Gruppen
Keine Informationen zu Gruppen vorhanden. |
Einschränkungen
Keine zusätzlichen Belegungseinschränkungen vorhanden. |