Graduate study programme

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Intelligent Transportation Systems DA4R4I-10

ECTS 5 | P 30 | A 0 | L 30 | K 0 | ISVU 149744 177087 177880 | Academic year: 2019./2020.

Course groups

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Course lecturers



Introduce students to the field of intelligent transport systems with an emphasis on VANETs (Vehicular Ad-hoc Networks). Teach and train students to develop, implement and evaluate algorithms for efficient information dissemination among vehicles and infrastructure in VANETs.

Conditions for enrollment

Requirements met for enrolling in the second year of the study programme

Course description

Introduction to basic principles and challenges in intelligent transport systems. Intelligent roads and traffic infrastructure. Overview of new technologies built into vehicles (architecture, embedded systems, operating systems, communication devices). Autonomous driverless vehicles. Information dissemination in VANETs (applications, concepts). Safety of communication, vehicles and pedestrians. Algorithms and protocols for efficient information dissemination among vehicles. Simulation of traffic and communication between vehicles and infrastructure using Omnet ++, Veins and SUMO simulators. Processing obtained results and performance evaluation.

Student requirements

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Monitoring of students

Defined by the Student evaluation criteria of the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek and paragraph 1.9

Obligatory literature

1. 1 Sommer, C; Dressler, F. Vehicular Networking Cambridge University Press, 2014.

2. 2 Bošnjak, I. INTELIGENTNI TRANSPORTNI SUSTAVI - ITS 1. Zagreb: Fakultet prometnih znanosti, Sveučilište u Zagrebu, 2006.

Pretraži literaturu na:

Recommended additional literature

1. 1 S. Ghosh, T. S. Lee Intelligent Transportation Systems: Smart and Green Infrastructure Design, Second Edition CRC Press, 2010

2. 2 R. Popescu-Zeletin, I. Radusch, M. Rigani Vehicular-2-X Communication: State-of-the-Art and Research in Mobile Vehicular Ad hoc Networks Springer, 2010

3. 3 M. Picone, S. Busanelli, M. Amoretti, F. Zanichelli, G. Ferrari Advanced Technologies for Intelligent Transportation Systems Springer, 2014

4. 4 J. Balen Učinkovito rasprostiranje poruka u mrežama vozila zasnovano na njihovom položaju doktorska disertacija, Osijek, Elektrotehnički fakultet, 2014.

5. 5 C. Sommer, F. Dressler Progressing Toward Realistic Mobility Models in VANET Simulations IEEE Communications Magazine, vol. 46 (11), pp. 132-137, studeni 2008.

Course assessment

Conducting university questionnaires on teachers (student-teacher relationship, transparency of assessment criteria, motivation for teaching, teaching clarity, etc.). Conducting Faculty surveys on courses (upon passing the exam, student self-assessment of the adopted learning outcomes and student workload in relation to the number of ECTS credits allocated to activities and courses as a whole).

Overview of course assesment

Learning outcomes
Upon successful completion of the course, students will be able to:

1. identify basic principles and challenges in Intelligent Transport Systems

2. explain the benefits of new technologies embedded in vehicles and transportation infrastructure

3. analyse, compare and evaluate various information dissemination approaches in VANETs

4. develop and implement algorithms for message dissemination in VANETs

5. conduct algorithm test by using traffic and network simulators

6. collect measurement results and evaluate the performance

Aktivnosti studenta: Vidi tablicu aktivnosti