Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Search result: Catalogue data in Autumn Semester 2016

Spatial Development and Infrastructure Systems Master Information
1. Semester
Major Courses
Major in Transport Planning
NumberTitleTypeECTSHoursLecturers
401-0647-00LIntroduction to Mathematical Optimization Information W5 credits2V + 1UD. Adjiashvili
AbstractIntroduction to basic techniques and problems in mathematical optimization, and their applications to problems in engineering.
ObjectiveThe goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering.
ContentTopics covered in this course include:
- Linear programming (simplex method, duality theory, shadow prices, ...).
- Basic combinatorial optimization problems (spanning trees, network flows, knapsack problem, ...).
- Modelling with mathematical optimization: applications of mathematical programming in engineering.
LiteratureInformation about relevant literature will be given in the lecture.
Prerequisites / NoticeThis course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics and more.
101-0417-00LTransport Planning MethodsW6 credits4GK. W. Axhausen
AbstractThe course provides the necessary knowledge to develop models supporting the solution of given planning problems. This is done by dividing the forecasting problem into sub-problems.
The course is composed of a lecture part, providing the theoretical knowledge, and a applied part, in which students develop their own models.
Objective- Knowledge of methods and algorithms commonly used in transport planning
- Ability to independently develop a transport model able to solve / answer the given problem / questions
- Understanding of algorithms and their implementations commonly used in transport planning
ContentThe course provides the necessary knowledge to develop models supporting the solution of given planning problems. Examples of such planning problems are the estimation of traffic volumes, prediction of estimated utilization of new public transport lines, and evaluation of effects (e.g. change in emissions of a city) triggered by building new infrastructure and changes to operational regulations.

To cope with the forecasting problem it is first divided into sub-problems. Then, these are solved using various algorithms like iterative proportional fitting, shortest path algorithms and the method of successive averages.

The course is composed of a lecture part, providing the theoretical knowledge, and a applied part, in which students create their own models. This part takes place in form of a tutorial and consists in the development of a computer program. The programming part is closely guided and particularly suitable for students with little programming experience.
Lecture notesThe slides of the lecture are provided electronically.
LiteratureWillumsen, P. and J. de D. Ortuzar (2003) Modelling Transport, Wiley, Chichester.

Cascetta, E. (2001) Transportation Systems Engineering: Theory and Methods, Kluwer Academic Publishers, Dordrecht.

Sheffi, Y. (1985) Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods, Prentice Hall, Englewood Cliffs.
363-1047-00LEconomics of Urban TransportationW3 credits2GA. Russo
AbstractThe first part of the course will present some basic principles of transportation economics, applied to the main issues in urban transport policy (e.g. road pricing, public transport tariffs, investment in infrastructure etc.). The second part of the course will consider some case studies where we will apply the tools acquired in the first part to actual policy issues.
ObjectiveThe main objective of this course is to provide students with some basic tools to analyze transport policy decisions from an economic perspective. Can economics help us reduce road congestion problems? Should drivers be asked to pay for using urban roads? Should public transport tariffs depend on how roads are priced? How should the investment in transport infrastructure be financed? These are some of the questions that students should be able to tackle after completing the course.
ContentCOURSE OUTLINE (preliminary):

1. Introduction
2. Travel demand :
a. travel cost and value of time
b. mode choice
3. Road congestion and first-best pricing
a. Static congestion model
b. Dynamic congestion models
c. Examples: London Congestion Charge, Stockholm Congestion Charge
4. Second-best pricing
a. Pricing roads with unpriced alternatives. Examples: tolled and toll-free highways
b. Public transport: pricing with road congestion and with (or without) road tolls
5. Investment in infrastructure: public transport and roads
a. Roads: Investment with and without pricing
b. induced demand
c. Economies of scale/density in public transport
6. Topics:
a. Political economy of road pricing: why do we see road pricing in so few cities (London, Stockholm...) and not in many other cities (NYC, Manchester, Paris...)?
b. What are the alternatives to road pricing to reduce congestion? Parking tariffs, traffic regulation (speed bumps, low emission zones), road space reduction. Examples: Zurich, San Francisco (SFPark), Paris.
c. Transport and land use: value of housing and transport services. Road congestion, transport subsidies and urban sprawl.
Lecture notesCourse slides will be made available to students prior to each class.
LiteratureSYLLABUS (preliminary):

course slides will be made available to students.

Additional material:

Part 1 to 5: textbook: Small and Verhoef (The economics of urban transportation, 2007).

Part 6: Topics to be covered on research papers/case studies.
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