Smart mobility

1.

Subject title

Smart mobility

Паметна мобилност (Smart mobility)

2.

Code

m23_s_077

3.

Study program

Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Eco-informatics, Inteligent Systems, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software Engineering, Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Statistics and Data Analytics, Data science in computer science and engineering, Еducation with ICT, Software Engineering, Software for embedded systems,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Сашо Граматиков

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

The cities experience a huge expansion that entails an increased need for mobility. The enormous growth of mobility is one of the key factors for pollution and security in cities. The main solution to these problems is the introduction of the concept of smart mobility aimed at reducing the number of vehicles by optimizing their routes and spare, intermodability of means of transport and sharing. Vehicle automation and their autonomy not only introduce greater safety, but also allow mobility to be offered as a service that reduces transportation costs and reduces the average travel time. The main goals of the subject will be to work out all concepts arising from smart mobility as well as the technical needs for communicating between mobile nodes for its implementation.

11.

Subject content:

Establish communication between vehicles and infrastructure (Vehicle-to-X) Ad hoc networks from vehicles (Vanets) Use of IoT for smart mobility Use of data from smart mobility Measurement and comparison of mobility Mobility as service (Maas) Intermodal transport Smart Billing at Mobility (Smart Ticketing) Autonomous vehicles Mobility simulation

12.

Learning methods:

NULL

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 45 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

45 hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

0 points

17.4.

Final exam

0 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

NULL

20.

Language of instruction

21.

Quality assurance method

NULL

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature