Intelligent systems in transportation technology
Description: The discipline studies intelligent systems installed in transport machinery. There are considered the types and purposes of intelligent systems, principles of their operation, design features and interface for managing systems. Students study methods of managing intelligent systems, acquire skills in testing their functions and assessing their performance. They study the possibilities of expanding the functionality of intelligent systems and methods for increasing their efficiency.
Amount of credits: 5
Пререквизиты:
- Prognostication & Expert Judgement of Transport & Transport Engineering
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 15 |
| Practical works | 30 |
| Laboratory works | |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 75 |
| SAW (Student autonomous work) | 30 |
| Form of final control | Exam |
| Final assessment method | exam |
Component: Component by selection
Cycle: Base disciplines
Goal
- Mastering intelligent systems in vehicles
Objective
- explore the types and functionality of intelligent systems in vehicles
Learning outcome: knowledge and understanding
- know the types and understand the functionality of intelligent systems in electric and hybrid vehicles
Learning outcome: applying knowledge and understanding
- use the functionality of intelligent systems in vehicles
Learning outcome: formation of judgments
- form a judgment about the potential capabilities of intelligent systems in vehicles
Learning outcome: communicative abilities
- communicate with intelligent systems in vehicles
Learning outcome: learning skills or learning abilities
- practical skills in the use of intelligent systems in vehicles and the ability for in-depth learning
Teaching methods
Dual education - the connection between theoretical training and practical skills in production
Assessment of the student's knowledge
Teacher oversees various tasks related to ongoing assessment and determines students' current performance twice during each academic period. Ratings 1 and 2 are formulated based on the outcomes of this ongoing assessment. The student's learning achievements are assessed using a 100-point scale, and the final grades P1 and P2 are calculated as the average of their ongoing performance evaluations. The teacher evaluates the student's work throughout the academic period in alignment with the assignment submission schedule for the discipline. The assessment system may incorporate a mix of written and oral, group and individual formats.
| Period | Type of task | Total |
|---|---|---|
| 1 rating | 1 exercise | 0-100 |
| 2 exercise | ||
| test | ||
| 2 rating | 3 exercise | 0-100 |
| 4 exercise | ||
| test | ||
| Total control | Exam | 0-100 |
The evaluating policy of learning outcomes by work type
| Type of task | 90-100 | 70-89 | 50-69 | 0-49 |
|---|---|---|---|---|
| Excellent | Good | Satisfactory | Unsatisfactory | |
| training | The work was completed in full, carefully, with the necessary explanations; the initial data are given; calculation results, units of measurement; conclusions. | The work was completed in full with minor comments, neatly; with the necessary explanations; the initial data are given; calculation results, units of measurement; conclusions. | The work was done with errors, not carefully enough; there are no necessary explanations; no source data; calculation results, units of measurement or conclusions. | The work was completed in full, carefully, with the necessary explanations; the initial data are given; calculation results, units of measurement; conclusions. |
| testing | 100-90% correct answers | 89-70% correct answers | 69-50% correct answers | 100-90% correct answers |
| exam | 1. Correct and complete answers to all theoretical questions are given; 2. The problem is completely solved; 3. The material is presented competently in compliance with a logical sequence | 1. Correct, but incomplete answers to all theoretical questions were given, minor errors or inaccuracies were made; 2. The problem was solved, but a minor error was made; 3. The material is presented competently in compliance with logical sequence. | 1. The answers to theoretical questions are correct in principle, but incomplete, there are inaccuracies in formulations and logical errors; 2. The problem is solved, but not completely; 3. The material is presented correctly, but the logical sequence is broken. | 1. Correct and complete answers to all theoretical questions are given; 2. The problem is completely solved; 3. The material is presented competently in compliance with a logical sequence |
Evaluation form
The student's final grade in the course is calculated on a 100 point grading scale, it includes:
- 40% of the examination result;
- 60% of current control result.
The final grade is calculated by the formula:
| FG = 0,6 | MT1+MT2 | +0,4E |
| 2 |
Where Midterm 1, Midterm 2are digital equivalents of the grades of Midterm 1 and 2;
E is a digital equivalent of the exam grade.
Final alphabetical grade and its equivalent in points:
The letter grading system for students' academic achievements, corresponding to the numerical equivalent on a four-point scale:
| Alphabetical grade | Numerical value | Points (%) | Traditional grade |
|---|---|---|---|
| A | 4.0 | 95-100 | Excellent |
| A- | 3.67 | 90-94 | |
| B+ | 3.33 | 85-89 | Good |
| B | 3.0 | 80-84 | |
| B- | 2.67 | 75-79 | |
| C+ | 2.33 | 70-74 | |
| C | 2.0 | 65-69 | Satisfactory |
| C- | 1.67 | 60-64 | |
| D+ | 1.33 | 55-59 | |
| D | 1.0 | 50-54 | |
| FX | 0.5 | 25-49 | Unsatisfactory |
| F | 0 | 0-24 |
Topics of lectures
- Intelligent ADAS and vehicle safety
- Computing technologies in autonomus vehicles
- Overview of intelligent technologies and solutions for ADAS
- Flash memory and NAND technologies
- Internet technologies IoV and Internet-connected cars
- Cameras and intelligent all-round view systems in modern vehicles
- Intelligent systems for recognizing the surrounding environment based on Radar technologies
- Intelligent systems for recognizing the environment based on Lidar technologies
- Intelligent power systems for modern cars
- Power management of plug-in electric vehicles in Smart Grids
- Intelligent drive systems and modern motor-wheels
- Automotive display technology
- Disk for storing data in the data center
- Role and Responsibilities of the Equipment Reliability Engineer
- Failure analysis in ADAS
Key reading
- 1. Autonomous Vehicles: Intelligent Transport Systems and Smart Technologies (Engineering Tools, Techniques and Tables) by Nicu Bizon, Lucian Dascalescu, Naser Mahdavi Tabatabaei. Nova Science Pub Inc., 2014. 544 Pages. ISBN: 978-1-63321-324-1 2. Yan Li, Hualiang Shi. Advanced Driver Assistance Systems and Autonomous Vehicles. From Fundamentals to Applications. Springer Nature Singapore, January 2022. 629 Pages. ISBN 978-9-81-195052-0, ISBN 978-9-81-195053-7 (eBook). DOI 10.1007/978-981-19-5053-7 3. Vehicular Communications for Smart Cars: Protocols, Applications and Security Concerns. By Niaz Chowdhury, Lewis Mackenzie. 1st Edition. Boca Raton, CRC Press, 2021. 216 Pages. ISBN 9781315110905 (eBook). DOI: https://doi.org/10.1201/9781315110905
Further reading
- 4. Khare, M.D., Raghavendra, R. (2024). Exploring Sensor Technologies and Automation Levels in Autonomous Vehicles. In: Verma, O.P., Wang, L., Kumar, R., Yadav, A. (eds) Machine Intelligence for Research and Innovations. MAiTRI 2023. Lecture Notes in Networks and Systems, vol 831. Springer, Singapore. https://doi.org/10.1007/978-981-99-8135-9_26 5. Горев, А. Э. Информационные технологии на транспорте : учебник для вузов / А. Э. Горев. — 3-е изд., перераб. и доп. — Москва : Издательство Юрайт, 2024. — 314 с. — (Высшее образование). — ISBN 978-5-534-17349-9. 6. Amit Kumar Tyagi, Niladhuri Sreenath. Intelligent Transportation Systems: Theory and Practice. Springer Singapore. 2022. 391 Pages. ISBN 978-981-19-7621-6. ISBN 978-981-19-7622-3 (eBook). DOI: https://doi.org/10.1007/978-981-19-7622-3
