With the advent of artificial engineering, there are rapid developments in the automotive sector, which is changing rapidly. The future of transport will be decided by new autonomous technologies being developed globally by different vehicle manufacturers. Automated vehicles will increase traffic efficiency, reduce stress on drivers, reduce environmental pollution, and open new avenues in the public transport system. Thus, a career in autonomous vehicle engineering will open exciting student opportunities.
The degree program in autonomous vehicles engineering deals with the interaction between the latest developments in sensor technology, electronics, machine learning and automobile engineering. The prospective students will acquire skills in an area that characterizes autonomous mobility systems. It can be broadly described as following phases
- Sense: Use of sensors for detecting environmental conditions
- Think: Analysis of data captured by sensors and using algorithms to create a driving strategy
- Act: As per analysis, the pre-determined driving strategy is implemented to have a safe ride
The concepts in above mentioned phases are taught exhaustively, and a strong foundation is built for students to learn future technologies in the field. Practical and methodological training is essential, along with teaching students theoretical concepts. Several project works are assigned to students so that practical implications of autonomous mobility are enriched among them. This will make prospective students ready for future assignments in the job market.
The degree program is four years of duration. All the classes will be carried out on campus. The language of teaching is English. The classroom will contain students from different geographies, and this helps in making them learn active cooperation, a trait necessary to survive in a competitive market.
The curriculum is divided into full eight semesters and covers the following modules:
| Semester | modules covered |
| 1 | Transport System Optimization, Foundations of Engineering Sciences, Programming 1,Foundations of Computer Science, Mathematics1
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| 2 | Electronics, Signals and Measurement, Programming 2, Algorithms and Data Structures, Statistics, Mathematics 2
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| 3 | Human Factors, Human-Computer Interaction and ADAS Systems, General Elective , Digital Signal Processing, Modeling and Simulation, Vehicle Dynamics, Model-based SW-Engineering
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| 4 | Scientific Seminar, Control Engineering, Vehicle Electronics and Vehicle Communication Networks, Foundations of Machine Learning, SW-Development Processes
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| 5 | Vehicle-to-X-Communication, Project, Sensor Data Processing and Sensor Data Fusion, Planning and Decision Making Algorithms, Vehicle Actuators |
| 6 | Path Planning, Autonomy and Decision Making, Business Management, PLV, Python, SQL |
| 7 | Vehicle Design Powertrain and Performance, Scientific Elective Subject 1, Scientific Elective Subject 2, Scientific Elective Subject 3, Bachelor’s Thesis, Thesis Seminar
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| 8 | Internship in reputed company
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