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Transport Planning Methods
Last Updated: 2026-02-05 16:30:42
Abstract
The course provides the necessary knowledge to develop models to understand, to support and to evaluate the solution of given planning problems.The course is composed of a lecture part, providing the theoretical knowledge, and an applied part in which students develop their own models in order to evaluate a transport project/policy.
Objective
- Appraise the role of theory and data in transport planning - Differentiate and appraise different transport planning methods (causality, 4 stage and agent based modeling, cost-benefit analysis) - Construct a transport model by statistical methods and algorithms commonly used in transport planning - Propose a modeling framework to analyze transport planning challenges. a decision-making supporting tool
Content
The course provides the necessary knowledge to develop models to understand travel behaviour and travel demand, and to support the solution of given planning problems. It also introduces cost-benefit analysis as a decision-making tool. 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 that, the problem is divided into sub-problems, which are solved using various statistical models and algorithms. The course is composed of a lecture part, providing the theoretical knowledge, and an applied part in which students develop their own models in order to analyse travel behaviour, develop a traditional transport model and to evaluate a transport project/ policy by means of cost-benefit analysis. Regular lab session take place to guide and support students with the applied part of the course.
Resources
Lecture Notes
Moodle platform (enrollment needed)
Literature
Willumsen, P. and J. de D. Ortuzar (2024) Modelling Transport, Wiley, Chichester. Van Wee, B., Annema, J.A., Banister, D. and Pudāne, B. (2023) The Transport System and Transport Policy, An Introduction. Second Edition. Cheltenham, UK • Northampton, MA, USA Pearl, J., Glymour, M., and Jewell N.P. (2016) Causal Inference in Statistics. Wiley and Sons. 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. Other: Schnabel, W. and D. Lohse (1997) Verkehrsplanung, 2. edn., vol. 2 of Grundlagen der Strassenverkehrstechnik und der Verkehrsplanung, Verlag für Bauwesen, Berlin. McCarthy, P.S. (2001) Transportation Economics: A case study approach, Blackwell, Oxford.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Transport Planning Methods |
|
4 h weekly |
Offered In
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Application Area (Only necessary and eligible for the Master degree in Applied Mathematics. One of the application areas specified must be selected for the category Application Area for the Master degree in Applied Mathematics. At least 8 credits are required in the chosen application area. Credits from other application areas cannot be recognised for further application areas.)
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