Skip to main content
About course

AH2204 Advanced Transport Modelling 7.5 credits

Administer About course

Transport models are used in many contexts to analyse policies and their effects, such as effects on emissions, cost and benefit, redistribution or effects on accidents. Policy examples include new roads, intelligent transport systems, new public transportation, increased or decreased cost for private car or public transportation, and flexible hours for shopping, working or schools. After the course, the student should be able to program a transport demand model and understand its limitations, and use a model to analyse a current policy measure, such as congestion charging.

Course offerings are missing for current or upcoming semesters.
Headings with content from the Course syllabus AH2204 (Autumn 2007–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

  • Theory for discrete choices, stochastic utility maximization, econometric estimation, entropy methods and gravity model.
  • Theory and algorithms for network equilibrium
  • Cost benefit valuation and effect evaluations: accidents, emissions and value of time.
  • Literature seminar

First, the theory is presented within lectures, which are the followed up by computer assignments, normally four.

Finally, in a literature study assignment, the student will search information to find a solution to a given problem. The suggested solution will be presented as a written report and at a seminar.

Intended learning outcomes

After completing the course, the student should be able to

  • use the theory for discrete choices and stochastic utility maximization to formulate models related to transport demand, in particular travel frequencies, destination choice and mode choice
  • program a transport forecasting model for analysing a real and current policy measure, such as congestion charges
  • account for models and theory for route choice
  • explain network equilibrium models and equivalent optimization formulations. Account for pros and cons with the concept of network equilibrium
  • use software for network equilibrium on a real world application to analyse traffic flows.
  • use decision support systems to analyse realistic planning problems
  • search relevant literature for a current application within transport demand modelling

Literature and preparations

Specific prerequisites

Knowledge of mathematical models, as defined by mathematical courses mandatory within the programs for Civil Engineering and Urban Management (Traffic Engineering), Engineering Physics (Optimisation and Systems Theory), Vehicle Engineering or Mechanical Engineering (Systems Engineering). The course Traffic Demand Forecasting is recommended

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

Hensher, D.A., and Button, K.J., 2000, Handbook of Transport Modelling, Pergamon Press. In particular chapters 1, 3, 5, 9, 10, 13, 17, and 19.

Train, K., 2003, * Discrete choice methods with simulation*, Cambridge University Press.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • INL1 - Assignments, 3.0 credits, grading scale: A, B, C, D, E, FX, F
  • TEN1 - Examination, 4.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade

Written exam (4,5 hp) and assignments (3 hp).

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Built Environment

Education cycle

Second cycle

Add-on studies

Mathematical economics, Probability theory, Optimization modelling. Applications within the programs for Urban Planning and Traffic Engineering