Subject Datasheet
Completion requirements
Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Intelligent Transportation Systems
1.2 Code
BMEEOFTMSFGG04-00
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 1 |
| Lab | 2 |
1.5 Evaluation
Midterm grade
1.6 Credits
5
1.7 Coordinator
| name | Dr. Lovas Tamás |
| academic rank | Associate professor |
| lovas.tamas@emk.bme.hu |
1.8 Department
Department of Photogrammetry and Geoinformatics
1.9 Website
1.10 Language of instruction
hungarian
1.11 Curriculum requirements
Compulsory in the Land Surveying and Geoinformatics (MSc) programme
1.12 Prerequisites
1.13 Effective date
1 September 2025
2. Objectives and learning outcomes
2.1 Objectives
The main objective of the course is to provide students with an in-depth knowledge of the civil engineering discipline of Intelligent Transport Systems. They will learn about the international regulatory framework, data, data collection and data storage technologies used in ITS. Lectures will introduce the range of data collected from infrastructure and vehicles, vehicle navigation methods, self-driving car technologies. In the exercises, students will work on project tasks and gain insight into the challenges and methods of data mining and processing. During the semester, students will gain first-hand experience of the industrial application of Intelligent Transport Systems through guest lectures and/or visits to industrial partners.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
1. Is familiar with the main international regulations on Intelligent Transport Systems (ITS).
2. Has an overview of ITS applications.
3. Has an overview of the data mining technologies used in ITS.
4. Is aware of some ITS mapping standards.
5. Has knowledge of the principles of operation of on-board sensor systems.
6. Has a contextual understanding of the potential applications of geographic information technology in ITS.
7. Is familiar with the basic technical characteristics of the communication technologies used in ITS.
B. Skills
1. Is able to select the appropriate data collection technology for different tasks used in ITS.
2. Performs primary data processing of sensor data.
3. Stores location data in spatial information structures.
4. Displays the processed data and results on maps.
5. Presents the main topics of the subject orally and in writing in a concise manner, using the correct terminology.
C. Attitudes
1. Collaborates with the instructor and fellow students to expand knowledge.
2. Tries to contribute proportionately when working in a team.
3. Strives to produce accurate mapping outputs.
4. Attends project consultations, arriving on time to take part in the collaborative work.
D. Autonomy and Responsibility
1. Independently carries out the tasks and parts of tasks assigned to him/her in the project assignment.
2. In the case of criticism of his/her work by teachers and students, he/she accepts well-founded critical comments and incorporates them into his/her further work.
3. Cooperates with fellow students in solving tasks in common parts of project tasks (e.g. data collection).
4. Actively participates in professional discussions during the presentation of project tasks.
5. Expresses his/her opinion with reasons.
2.3 Methods
Lectures and project-based, consultative labs. Attendance is compulsory for 70% of the contact hours, some labs cannot be missed and must be made up. The software required for the completion of the assignments is provided by the department.
2.4 Course outline
1. ITS objectives, economic role, EU directives, projects, basic concepts
2. Map, map content, infrastructure data and perception, position
3. Vehicle data and sensing; vehicle sensors
4. Communication
5. Vehicle and pedestrian navigation, geospatial analysis of traffic data
6. Data processing: graph analysis, traffic data processing, geospatial analysis of traffic data
7. Partial summary
8. application of Intelligent Transport Systems (ITS) in Hungary
9. ITS applications in pedestrian movement detection and support
10. ITS trends in Europe
11. Road ITS applications I.
12. Road ITS applications II.
13. practical project task presentation, discussion I.
14. Practical project task presentation, discussion II.
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
Downloadable material: https://edu.epito.bme.hu
2.6 Other information
The subject may include a group visit to an industrial partner.
2.7 Consultation
As indicated on the department's website or by prior arrangement by e-mail; e-mail: lovas.tamas@emk.bme.hu
This Subject Datasheet is valid for:
2025/2026 semester II
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
The assessment of the learning outcomes set out in 2.2 is based on a midterm test, a home assignment and active participation in labs and consultations.
3.2 Assessment methods
| Assessment Name (Type) | Code | Assessed Learning Outcomes |
|---|---|---|
| midterm test | MT | A.1-A.7; B.5 |
| home assignment | HW | A.1-A.7; B.1-B.5; C.3; D.1-D.2 |
| active participation | A | C.1-C.2, C.4; D.1-D.5 |
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 |
|---|---|
| MT | 45% |
| HW | 40% |
| A | 15% |
| Total | 100% |
3.4 Requirements and validity of signature
No signature can be obtained in the subject.
3.5 Grading system
| Grade | Score (P) |
|---|---|
| excellent (5) | 90≤P |
| good (4) | 80≤P<90% |
| satisfactory (3) | 65≤P<80% |
| pass (2) | 50≤P<65% |
| fail (1) | P<50% |
3.6 Retake and repeat
1) The midterm test can be made up during the make-up week.
2) The home assignment may be submitted late, subject to the payment of a fee as specified in the regulations, until 16:00 on the last day of the make-up period or sent electronically until 23:59.
3) Home assignment submitted and accepted may be corrected free of charge up to the deadline and in the manner specified in 2)).
4) Due to its nature, active participation cannot be replaced, corrected or otherwise substituted or replaced.
3.7 Estimated workload
| Activity | Hours/Semester |
|---|---|
| attending contact hours | 14 |
| preparation to labs | 10×6=60 |
| preparation to assessments | 26 |
| preparing home assignment | 50 |
3.8 Effective date
1 September 2025
This Subject Datasheet is valid for:
2025/2026 semester II