Francesco Corman: Catalogue data in Spring Semester 2021 |
| Name | Prof. Dr. Francesco Corman |
| Field | Transport Systems |
| Address | Professur für Transportsysteme ETH Zürich, HIL F 13.1 Stefano-Franscini-Platz 5 8093 Zürich SWITZERLAND |
| Telephone | +41 44 633 33 50 |
| francesco.corman@ivt.baug.ethz.ch | |
| Department | Civil, Environmental and Geomatic Engineering |
| Relationship | Associate Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 101-0459-00L | Logistics and Freight Transportation | 6 credits | 4G | F. Corman, K. Brossok, D. Bruckmann, M. Ruesch, T. Schmid, A. Trivella | |
| Abstract | Basics and concepts of logistics and freight transport; offers, infrastructure and production processes of different transport systems; regulatory framework | ||||
| Learning objective | Identification and understanding the interconnections between logistic requirements, market, transport offers, operational processes, transport means and regulation in freight transport of all transport systems (road, rail, intermodal, waterborne and air). | ||||
| Content | Basics and concepts of logistics, actors in logistics and freight transport, transport demand (1) in-house logistics, storage, transport safety, dangerous goods (2), basics to transport offers, production processes and infrastructure for road, rail, intermodal, waterborne (sea and inland waterways) and air transport, urban logistics (3), transport policy, regulation, spatial planning, location issues and network design with optimization methods (4) | ||||
| Lecture notes | Lecture slides in German or English will be provided. | ||||
| 101-0522-10L | Doctoral Seminar Data Science and Machine Learning in Civil, Env. and Geospatial Engineering  Number of participants limited to 21. | 1 credit | 2S | B. Soja, E. Chatzi, F. Corman, O. Fink, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, M. J. Van Strien | |
| Abstract | Current research in machine learning and data science within the research fields of the department. The goal is to learn about current research projects at our department, to strengthen our expertise and collaboration with respect to data-driven models and methods, to provide a platform where research challenges can be discussed, and also to practice scientific presentations. | ||||
| Learning objective | - learn about discipline-specific methods and applications of data science in neighbouring fields - network people and methodological expertise across disciplines - establish links and discuss connections, common challenges and disciplinespecific differences - practice presentation and discussion of technical content to a broader, less specialised scientific audience | ||||
| Content | Current research at D-BAUG will be presented and discussed. | ||||
| Prerequisites / Notice | This doctoral seminar is intended for doctoral students affiliated with the Department of Civil, Environmental and Geomatic Engineering. Other students who work on related topics need approval by at least one of the organisers to register for the seminar. Participants are expected to possess elementary skills in statistics, data science and machine learning, including both theory and practical modelling and implementation. The seminar targets students who are actively working on related research projects. | ||||
| 101-0523-11L | Frontiers in Machine Learning Applied to Civil, Env. and Geospatial Engineering (FS21) Number of participants limited to 21. | 1 credit | 2S | M. Lukovic, E. Chatzi, F. Corman, O. Fink, I. Hajnsek, M. A. Kraus, K. Schindler, B. Soja, M. J. Van Strien | |
| Abstract | This doctoral seminar organised by the D-BAUG platform on data science and machine learning aims at discussing recent research papers in the field of machine learning and analyzing the transferability/adaptability of the proposed approaches to applications in the field of civil and environmental engineering (if possible and applicable, also implementing the adapted algorithms). | ||||
| Learning objective | Students will • Critically read scientific papers on the recent developments in machine learning • Put the research in context • Present the contributions • Discuss the validity of the scientific approach • Evaluate the underlying assumptions • Evaluate the transferability/adpatability of the proposed approaches to own research • (Optionally) implement the proposed approaches. | ||||
| Content | With the increasing amount of data collected in various domains, the importance of data science in many disciplines, such as infrastructure monitoring and management, transportation, spatial planning, structural and environmental engineering, has been increasing. The field is constantly developing further with numerous advances, extensions and modifications. The course aims at discussing recent research papers in the field of machine learning and analyzing the transferability/adaptability of the proposed approaches to applications in the field of civil and environmental engineering (if possible and applicable, also implementing the adapted algorithms). Each student will select a paper that is relevant for his/her research and present its content in the seminar, putting it into context, analyzing the assumptions, the transferability and generalizability of the proposed approaches. The students will also link the research content of the selected paper to the own research, evaluating the potential of transferring or adapting it. If possible and applicable, the students will also implement the adapted algorithms The students will work in groups of three students, where each of the three students will be reading each other’s selected papers and providing feedback to each other. | ||||
| Prerequisites / Notice | This doctoral seminar is intended for doctoral students affiliated with the Department of Civil, Environmental and Geomatic Engineering. Other students who work on related topics need approval by at least one of the organisers to register for the seminar. Participants are expected to possess elementary skills in statistics, data science and machine learning, including both theory and practical modelling and implementation. The seminar targets students who are actively working on related research projects. | ||||
| 103-0230-00L | Transportation Engineering Lab | 6 credits | 2G | A. Kouvelas, F. Corman, N. Garrick | |
| Abstract | The goal is to integrate the contents of the lectures of the block “Transportation” through a joint set of exercises which will allow the students to understand how the parts come together in the design of transport systems. The exercise will be based on a Swiss city. The exercises will involve onsite work. | ||||
| Learning objective | - Diese gemeinsame Übung an Hand einer Schweizer Ortschaft dient der Vertiefung des Verständnisses der Wechselwirkungen zwischen allen Teilen des Verkehrssystems - Die Studenten haben Gelegenheit durch die Gruppenarbeit ihre Fähigkeiten in der Zusammenarbeit zu üben - Den entwerferischen Aufgaben wird in allen Teilen besondere Aufmerksamkeit geschenkt (Netzentwurf, Liniennetzentwurf, Knoten und Strassenentwurf, Massnahmen des Nachfragemanagements) | ||||
| Content | Drei verknüpfte Übungen aus der Verkehrsplanung, Verkehrstechnik, und dem Öffentlichen Verkehr - Verkehrserhebungen - Strassenraumentwurf - Netzentwurf - Nachfrageberechnung - Fahrplanentwurf - Leistungsfähigkeitsberechnungen für die Strecken und Knoten - Bewertung | ||||
| 103-0414-AAL | Transport Basics Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit. | 4 credits | 9R | F. Corman | |
| Abstract | -Introduction to the fundamentals of transportation -Developing an understanding of the interactions between land use and transportation -Introduction to the dynamics of transport systems: daily patterns and historical developments | ||||
| Learning objective | Introduction to the fundamentals of transportation. | ||||
| Content | -Accessibility -Equilibrium in transport networks -Fundamental transport models -Traffic flow and control -Vehicle dynamics on rail and road -Transport modes and supply patterns -Time tables | ||||
| 103-0414-10L | Transport Basics | 4 credits | 3G | A. Kouvelas, F. Corman, N. Garrick | |
| Abstract | -Introduction to the fundamentals of transportation -Developing an understanding of the interactions between land use and transportation -Introduction to the dynamics of transport systems: daily patterns and historical developments | ||||
| Learning objective | -Introduction to the fundamentals of transportation -Developing an understanding of the interactions between land use and transportation -Introduction to the dynamics of transport systems: daily patterns and historical developments | ||||
| Content | -Introduction to the fundamentals of transportation -Developing an understanding of the interactions between land use and transportation -Introduction to the dynamics of transport systems: daily patterns and historical developments | ||||
| 149-0003-00L | Railway Infrastructures Does not take place this semester. Only for CAS and DAS in Transport Engineering | 5 credits | 1G | F. Corman | |
| Abstract | |||||
| Learning objective | Teaches the basic principles of public transport network and topology design, geometrical design, dimensioning and construction as well as the maintenance of rail infrastructures. In detail, fundamentals of railroad technology and interactions between track and vehicles, network development and infrastructure planning, planning of rail infrastructure, planning and design of railway stations, construction and dimensioning of tracks, approval and beginning service on complex infrastructure facilities, special issues of maintenance. Teaches students to recognize the interactions between the infrastructure design and the production processes. | ||||