342-0970/02 – Simulation of Transportation Systems (SDS)

Gurantor departmentInstitute of TransportCredits10
Subject guarantordoc. Ing. Michal Dorda, Ph.D.Subject version guarantordoc. Ing. Michal Dorda, Ph.D.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFSIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
DOR028 doc. Ing. Michal Dorda, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 25+0
Part-time Examination 25+0

Subject aims expressed by acquired skills and competences

The student is able to describe the modelled system and determine what data and the extent to which it needs to simulate the studied system. This data he / she can process by mathematical statistics tools. He / she is able to design a conceptual model and, based on this conceptual model, determine the appropriate type of simulation tool. He / she is able to create simulation models of transport systems in selected simulation environments. He / she can design experiments with simulation models and is able to evaluate the results of these experiments.

Teaching methods

Individual consultations
Project work


The subject develops and deepens the complex knowledge of methods used for simulation needs in order to model the discrete character processes in transport systems, regardless of the mode of transport. Students will be introduced to principles of simulation based on event-oriented algorithms as well as principles based on Petri networks and multiagent systems. The student will be able to assess the suitability of using simulation methods for the assessment of the model transport problem, to statistically process the necessary input data using the methods of mathematical statistics, to design effective conceptual and simulation models, to use optimization methods for the improvement of key operating parameters, which can characterize the efficiency of the simulated transport system in connection with valid legislation and current theoretical knowledge from the field of transport theory. From the field of special simulation methods, the student will be introduced to the possibilities of specialized software tools for transport planning purposes, such as (Aimsun, Omnitrans, etc.).

Compulsory literature:

ZEIGLER, Bernard P., PRAEHOFER, Herbert a KIM, Tag Gon. Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems. 2nd ed. San Diego: Academic Press, c2000. ISBN 0-12-778455-1. SOKOLOWSKI, John A. a BANKS, Catherine M., ed. Principles of modeling and simulation: a multidisciplinary approach [online]. Hoboken: John Wiley & Sons, 2008 [cit. 2018-01-10]. ISBN 978-0-470-40356-3.

Recommended literature:

Introduction to logistics systems planning and control [online]. Hoboken: Wiley, 2005 [cit. 2018-01-10]. ISBN 0-470-01404-0. BOLCH, Gunter. Queueing networks and Markov chains: modeling and performance evaluation with computer science applications. 2nd ed. Hoboken: Wiley, c2006. ISBN 0-471-56525-3.

Way of continuous check of knowledge in the course of semester

Oral examination.


Other requirements

Solution and defense of the project on the given topic.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1) Theory of Discrete Simulation Models. 2) Probability theory - discrete and continuous random variables used in simulation models and their description. 3) Theory of generating pseudorandom numbers - methods of generation, transformation methods, randomness tests. 4) Data preparation for simulation modeling needs - point estimation theory. 5) Data preparation for simulation models - tests of good agreement. 6) Methods for verifying and validating simulation models. 7) Software for discrete simulation of transport systems and processes. 8) Statistical processing of simulation results - interval estimates, hypothesis testing, regression and correlation analysis, sensitivity analysis. 9) Optimization methods in simulation. 10) Petri nets and their use for simulation of transport systems. 11) Multiagent systems and their use for simulation of transport systems.

Conditions for subject completion

Part-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Examination Examination  
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2021/2022 (P1041D040005) Transport Systems K English Ostrava Choice-compulsory type B study plan
2021/2022 (P1041D040005) Transport Systems P English Ostrava Choice-compulsory type B study plan
2020/2021 (P1041D040005) Transport Systems K English Ostrava Choice-compulsory type B study plan
2020/2021 (P1041D040005) Transport Systems P English Ostrava Choice-compulsory type B study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner