Francesco Corman: Catalogue data in Autumn Semester 2023

Name Prof. Dr. Francesco Corman
FieldTransport Systems
Address
Professur für Transportsysteme
ETH Zürich, HIL F 13.1
Stefano-Franscini-Platz 5
8093 Zürich
SWITZERLAND
Telephone+41 44 633 33 50
E-mailfrancesco.corman@ivt.baug.ethz.ch
DepartmentCivil, Environmental and Geomatic Engineering
RelationshipAssociate Professor

NumberTitleECTSHoursLecturers
101-0415-01LPublic Transport and Railways3 credits2GF. Corman
AbstractFundamentals of public and collective transport, in its different forms.
Categorization of performance dimensions of public transport systems, and their implications to their design and operations.
Learning objectiveTeaches the basic principles of public transport network and topology design, to understand the main characteristics and differences of public transport networks, based on buses, railways, or other technologies.
Teaches students to recognize the interactions between the infrastructure design and the production processes, and various performance criteria based on various perspective and stakeholders.
At the end of this course, students can critically analyze existing networks of public transport, their design and use; consider and substantiate different choices of technologies to suitable cases; optimize the use of resources in public transport.
ContentFundamentals: Infrastructures and vehicle technologies of public transport systems; interaction between track and vehicles; passengers and goods as infrastructure users; management and financing of networks.

Infrastructure: Planning processes and decision levels in network development and infrastructure planning, planning of topologies; tracks and roadways, station infrastructures; Fundamentals of the infrastructure design for lines; track geometries; switches and crossings

Vehicles: Classification, design and suitability for different goals
Network design: design dilemmas, conceptual models for passenger transport on long distance, urban regional transport.

Operations: Passenger/Supply requirements for line operations; timetabling, measures of realized operations, capacity
Lecture notesSlides, in English, are made available some days before each lecture.
LiteratureReference material books are provided in German and English (list disseminated at lecture), plus Skript Bahninfrastruktur; System- und Netzplanung
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingassessed
Media and Digital Technologiesfostered
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingfostered
Critical Thinkingfostered
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
101-0427-01LPublic Transport Design and Operations6 credits4GF. Corman, T.‑H. Yan
AbstractThis course aims at analyzing, designing, improving public transport systems, as part of the overall transport system.
Learning objectivePublic transport is a key driver for making our cities more livable, clean and accessible, providing safe, and sustainable travel options for millions of people around the globe. Proper planning of public transport system also ensures that the system is competitive in terms of speed and cost. Public transport is a crucial asset, whose social, economic and environmental benefits extend beyond those who use it regularly; it reduces the amount of cars and road infrastructure in cities; reduces injuries and fatalities associated to car accidents, and gives transport accessibility to very large demographic groups.

Goal of the class is to understand the main characteristics and differences of public transport networks.
Their various performance criteria based on various perspective and stakeholders.
The most relevant decision making problems in a planning tactical and operational point of view
At the end of this course, students can critically analyze existing networks of public transport, their design and use; consider and substantiate possible improvements to existing networks of public transport and the management of those networks; optimize the use of resources in public transport.

General structure:
general introduction of transport, modes, technologies,
system design and line planning for different situations,
mathematical models for design and line planning
timetabling and tactical planning, and related mathematical approaches
operations, and quantitative support to operational problems,
evaluation of public transport systems.
ContentBasics for line transport systems and networks
Passenger/Supply requirements for line operations
Objectives of system and network planning, from different perspectives and users, design dilemmas
Conceptual concepts for passenger transport: long-distance, urban transport, regional, local transport

Planning process, from demand evaluation to line planning to timetables to operations
Matching demand and modes
Line planning techniques
Timetabling principles

Allocation of resources
Management of operations
Measures of realized operations
Improvements of existing services
Lecture notesLecture slides are provided.
LiteratureCeder, Avi: Public Transit Planning and Operation, CRC Press, 2015, ISBN 978-1466563919 (English)

Holzapfel, Helmut: Urbanismus und Verkehr – Bausteine für Architekten, Stadt- und Verkehrsplaner, Vieweg+Teubner, Wiesbaden 2012, ISBN 978-3-8348-1950-5 (Deutsch)

Hull, Angela: Transport Matters – Integrated approaches to planning city-regions, Routledge / Taylor & Francis Group, London / New York 2011, ISBN 978-0-415-48818-4 (English)

Vuchic, Vukan R.: Urban Transit – Operations, Planning, and Economics, John Wiley & Sons, Hoboken / New Jersey 2005, ISBN 0-471-63265-1 (English)

Walker, Jarrett: Human Transit – How clearer thinking about public transit can enrich our communities and our lives, ISLAND PRESS, Washington / Covelo / London 2012, ISBN 978-1-59726-971-1 (English)

White, Peter: Public Transport - Its Planning, Management and Operation, 5th edition, Routledge, London / New York 2009, ISBN 978-0415445306 (English)
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingassessed
Media and Digital Technologiesfostered
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationassessed
Cooperation and Teamworkassessed
Customer Orientationassessed
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
101-0522-10LDoctoral Seminar Data Science and Machine Learning in Civil, Env. and Geospatial Engineering Restricted registration - show details 1 credit1SV. Ntertimanis, E. Chatzi, F. Corman, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, B. Soja, M. J. Van Strien
AbstractCurrent 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
ContentCurrent research at D-BAUG will be presented and discussed.
Prerequisites / NoticeThis 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.
101-0523-14LFrontiers in Machine Learning Applied to Civil, Env. and Geospatial Engineering1 credit1GV. Ntertimanis, E. Chatzi, F. Corman, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, B. Soja, M. J. Van Strien
AbstractThis 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 objectiveStudents 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.
ContentWith 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 / NoticeThis 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.
103-0377-10LBasics of RE&IS Restricted registration - show details 3 credits2GC. Sailer, F. Corman, D. Kaufmann
AbstractThe course Basics of RE&IS provides essential skills and knowledge for the Master's degree program in Spatial Development & Infrastructure Systems. Students will know the basics of scientific writing with complementary use of human and artificial intelligence. Students will learn how to search for scientific literature, create graphs, and give a presentation while writing a literature review.
Learning objectiveThe overall objective is to equip students with the necessary skills and knowledge to effectively conduct academic writing, specifically focused on writing a review article, and to introduce them to the use of Generative AI in enhancing their research and writing process.
By the end of the course, students should be able to independently;
- search for and evaluate high-quality sources on their chosen topic and use citation management software.
- organize their writing and construct a scientific text, paragraph, and sentence structure using coherent and complete arguments and clear, concise, and specific language.
- understand citation styles and subject conventions, apply references to the chosen reference system, and properly cite all types of sources.
- determine appropriate types of graphs to represent data and create and evaluate effective graphical representations of data.
- present results systematically and persuasively using a consistent, informative slide deck with engaging and accurate visualizations; speak clearly and confidently using effective words, voice, and body language; know how to practice and deliver the presentation.
- review and provide appropriate feedback on peer work, use AI tools to assist in various stages of the writing process, and critically reflect on originality declarations, plagiarism, etc.
ContentInvolved chairs are:
Infrastructure Management (IM), Transportation Systems (TS), Traffic Engineering (SVT), Transport Planning (VPL), Spatial Development and Urban Policy (SPUR), Planning of Landscape and Urban Systems (PLUS) and Spatial Transformation Laboratories (STL).

Christian Sailer, education developer at the D-BAUG, has a special focus on interdisciplinary competencies in teaching at the D-BAUG. He therefore takes the lead of this course in collaboration with RE&IS chairs, who periodically alternate among themselves.
Lecture notesAll documents relevant for the course (slides, literature, further links, etc.) are provided centrally via the Moodle platform.
LiteratureAmerican Psychological Association (APA) (2010) Publication Manual of the American Psychological Association, 6th edition, APA, Washington, D.C.
Axhausen, K.W. (2016) Style Guide for Student Dissertations, IVT, ETH Zürich, Zürich (available as download under learning materials)
Backhaus, N. and R. Tuor (2008): Leitfaden für wissenschaftliches Arbeiten, 7. überarbeitete und ergänzte Auflage. Schriftenreihe Humangeographie 18, Geographisches Institut der Universität Zürich, Zürich.
ZürichChapman, M. and C. Wykes (1996) Plain Figures, HM Stationary Office, London.
ETH (2017) Citation etiquette: How to handle the intellectual property of others, ETH, ETH Zürich, Zürich (last retrieved 29.11.2017)
Modern Language Association of America (MLA) (2016) MLA Handbook, 8th edition, MLA, New York.
Monmonier, M. (1991) How to lie with maps, University of Chicago Press, Chicago.
Tufte, E. R. (2001) The Visual Display of Quantitative Information, Graphics Press USA
Wilkinson, L. (1999) The Grammar of Graphics, Springer, Berlin.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesfostered
Media and Digital Technologiesfostered
Social CompetenciesCommunicationassessed
Cooperation and Teamworkfostered
Personal CompetenciesCreative Thinkingfostered
Critical Thinkingfostered
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
103-0414-AALTransport 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 credits9RF. 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 objectiveIntroduction 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
364-1058-00LRisk Center Seminar Series0 credits2SH. Schernberg, D. Basin, A. Bommier, D. N. Bresch, S. Brusoni, L.‑E. Cederman, P. Cheridito, F. Corman, H. Gersbach, C. Hölscher, K. Paterson, G. Sansavini, B. Stojadinovic, B. Sudret, J. Teichmann, R. Wattenhofer, S. Wiemer, R. Zenklusen
AbstractThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. Students and other guests are welcome.
Learning objectiveParticipants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop novel mathematical models for open problems, to analyze them with computers, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to work scientifically on an internationally competitive level.
ContentThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. For details of the program see the webpage of the colloquium. Students and other guests are welcome.
Lecture notesThere is no script, but a short protocol of the sessions will be sent to all participants who have participated in a particular session. Transparencies of the presentations may be put on the course webpage.
LiteratureLiterature will be provided by the speakers in their respective presentations.
Prerequisites / NoticeParticipants should have relatively good mathematical skills and some experience of how scientific work is performed.