Headings with content from the Course syllabus AH2174 (Autumn 2021–) are denoted with an asterisk ( )
Content and learning outcomes
Course disposition
This course extends to application of traffic simulation models for analysis of dynamic traffic systems: input data preparation, calibration, validation, analysis of simulation output. Case studies and examples are also given. Students will become familiar with existing traffic simulation models in traffic research and applications in practice (for example SUMO). Students will have hands-on experience with the use of traffic simulation models for alternatives analyses and evaluation through case studies and project work.
Assignments: Include two project works:
The examination: Oral exam
Course contents
This is an advanced course on transport simulation. It consists of lectures and exercises. The lectures are structured in two blocks of roughly equal size.
The first half of the lectures teaches fundamental concepts of simulation and its application in transport. This comprises: taxonomy of simulation approaches, scientific principles and mathematical simulation framework, input data preparation, computer simulation techniques, analysis of simulation outputs. These lectures provide a solid foundation to understand and use transport simulations.
The second half of the lectures treats a selection of more specific topics. This comprises: calibration and validation of simulators, experimental design, on-line simulation, simulation-based optimization. Students will have the opportunity to influence what topics the course focuses on. These lectures provide the ability to solve complex, real transport problems with simulation.
The exercises investigate several case studies of increasing realism with an operational traffic simulator. The largest part of the exercises is hands-on work with the simulation software. Intermediate classroom-type exercises deepen the understanding of concepts taught in the lectures and clarify their relation to the case studies. The exercises give students practical experience with a real simulation software.
Intended learning outcomes
In this course, students obtain fundamental knowledge on the principles and applications of transport simulations.
Transport simulators are complex computer programs that solve complex model systems. The models describe real transport phenomena, such as traffic flow dynamics in urban networks. They are typically solved through mathematical techniques, in particular stochastic simulation methods. Real transport problems are analyzed with free or commercial software implementations of these models and solvers.
After successful completition of the course, students should be able to
understand and apply the basic principles of simulation;
interpret and analyze stochastic simulation results;
select application-specific models and simulation methods;
collect and use real data to calibrate and validate transport simulators;
deploy simulations for scenario analysis, prediction, and optimization.
Literature and preparations
Specific prerequisites
Bachelor's degree or equivalent in civil engineering, geography, technical physics, computer science, statistics, economics, or mathematics.
At least 3 hp respectively in basic programming, linear algebra and numerical methods, as well as probability theory and statistics.
And Eng B/6 according to the Swedish upper secondary school system.
Equipment
No information inserted
Literature
S. M. Ross, Simulation, 4th edition, Elsevier, 2006
A. M. Law and W. David Kelton, Simulation Modeling and Analysis, 4rth edition,McGraw Hill, 2006.
R. Dowling, A. Skabardonis, and V. Alexiadis, Traffic Analysis Toolbox Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software, FHWA-HRT-04-040.
R. Roess, E. Prassas, and W. McShane, Traffic Engineering, 3rd edition, Prentice Hall, 2004.
S. Washington, M. Karlaftis, and F. Mannering, Statistical and Econometric Methods for Transportation Data Analysis, Chapman & Hall/CRC, 2003.
Selected papers and class notes
Manuals of traffic simulation software to be used for projects and case studies
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
PRO2 -
Project Assignments,
3.5 credits,
grading scale: A, B, C, D, E, FX, F
TEN2 -
Oral Examination,
4.0 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.
PRO1 - Assignments, 3.5 credits, grade scale: A, B, C, D, E, FX, F
TEN1 - Examination, 4.0 credits, grade scale: A, B, C, D, E, FX, F
Other requirements for final grade
A mandatory oral examination equivalent to 4.0 ECTS credits on the A-F grading scale and a mandatory project assignment equivalent to 3.5 credits with grading scale A-F. The course will be determined by the grade of both
Opportunity to complete the requirements via supplementary examination
No information inserted
Opportunity to raise an approved grade via renewed examination
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.
