Subject Datasheet
Completion requirements
Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Transport Modelling
1.2 Code
BMEEOUVMSFIN12-00
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 2 |
1.5 Evaluation
Midterm grade
1.6 Credits
3
1.7 Coordinator
| name | Dr. Juhász János Attila |
| academic rank | Associate professor |
| juhasz.janos@emk.bme.hu |
1.8 Department
Department of Highway and Railway Engineering
1.9 Website
1.10 Language of instruction
hungarian
1.11 Curriculum requirements
Recommended elective in the Specialization in Highway and Railway Engineering (MSc) programme
1.12 Prerequisites
1.13 Effective date
1 September 2025
2. Objectives and learning outcomes
2.1 Objectives
The course aims to introduce students to the basic transportation modelling concepts and methods. The aim is that during the semester, students will deepen their knowledge of using modern digital technologies to support planning. The aim is that students will get a comprehensive picture of transportation modelling tools and possibilities, as well as the operation and limitations of computational procedures. This is important because although the field does not have civil engineering roots, our students participating in today's Master's degree program and applying their knowledge in their profession will certainly come into contact with the results of this science during their careers.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
1. Knows the basic design principles and methods used in civil engineering practice.
2. Knows the fundamental relationships of traffic modelling.
3. Is aware of the purpose and limitations of traffic models.
4. Recognizes when it is necessary to apply which model.
5. Understands the workflows through which a traffic (macroscopic) model is built.
6. Is aware of the purpose and limitations of microscopic models.
7. Understands the workflows through which a microscopic simulation model is built.
8. Knows what results can be expected from applying traffic models.
B. Skills
1. Is able to recognize and interpret the results of a complex traffic model.
2. With minor guidance, is able to learn the structure and characteristics of a simple macroscopic model in such depth that it can be modified fundamentally.
3. Is able to independently determine the range of data necessary for the preparation of a macroscopic model.
4. Is able to independently determine the range of data necessary for the preparation of a microscopic model.
5. Is able to independently prepare a microscopic model of a simple intersection.
6. Is able to independently prepare a microscopic model of pedestrian traffic.
7. Is able to collect data on traffic characteristics using the microscopic model and evaluate them.
8. Is able to support settlement management tasks and civil engineering subtasks within the scope of settlement engineering activities.
C. Attitudes
1. Cooperates with the instructor and fellow students in expanding their knowledge.
2. Expands their knowledge and professional vocabulary through continuous learning.
3. Is open to the use of information technology tools.
4. Strives for precise and error-free task solving. 5. Strives for precise, professional wording in their expressions.
D. Autonomy and Responsibility
1. Prepares for class as needed, using the provided course materials, based on prior instruction from the instructor.
2. Prepares responsibly to successfully complete summative performance assessments.
3. Monitors legislative, technical, technological, and administrative changes related to the field.
4. Uses cognitive skills to make decisions and to logically move from one idea to another.
2.3 Methods
In addition to regular contact classes, the acquisition of subject competencies is facilitated by extracurricular tasks, the development of which is supported by short video films.
2.4 Course outline
1. Introduction to modeling. Basics of transportation modeling
2. Travel demands, mode choice, modal split
3. Introduction of macroscopic modeling
4. Presentation of PTV VISUM features
5. Case study: network model development
6. Case study: evaluation of network modifications
7. Introduction to microscopic traffic modeling
8. Presentation of PTV VISSIM features
9. Case study: intersection traffic flow analysing
10. Case study: intersection control – traffic lights
11. Case study: roundabout modeling
12. Case study: pedestrian traffic modeling
13. Road accident modeling using PC Crash
14. mid-term exam
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials
1. Documents that can be downloaded from the course website (lecture slides, data, etc.)
2. Juan de Dios Ortúzar, Luis G. Willumsen: Modelling Transport
3. Háznagy Andor: Közlekedési modellezés
2.6 Other information
Attendance at lectures is 70% mandatory. Students who miss four or more sessions cannot obtain credit for the course..
2.7 Consultation
2 hours per week, considering the correspondence course schedule.
This Subject Datasheet is valid for:
2025/2026 semester II
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
Learning outcomes are assessed based on active participation in lectures and mid-term results.
3.2 Assessment methods
| Assessment Name (Type) | Code | Assessed Learning Outcomes |
|---|---|---|
| mid-term tesr | MT1 | A.1-A.8, B.1-B.8, C.1-C.4, D.1-D.4 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Code | Weight |
|---|---|
| MT1 | 100% |
| Total | 100% |
3.4 Requirements and validity of signature
Signature can not be obtained for the course.
3.5 Grading system
| Grade | Score (P) |
|---|---|
| excellent (5) | 0≤P |
| good (4) | 0≤P<0% |
| satisfactory (3) | 0≤P<0% |
| pass (2) | 0≤P<0% |
| fail (1) | P<0% |
3.6 Retake and repeat
The midterm test can be repeated once during the semester. In case of a repeat, the new score will overwrite the previous score.
3.7 Estimated workload
| Activity | Hours/Semester |
|---|---|
| Participating at lessons | 14×2=28 |
| Preparing for midterm test | 62 |
3.8 Effective date
1 September 2025
This Subject Datasheet is valid for:
2025/2026 semester II