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Lecturer(s)
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Hlava Jaroslav, doc. Dr. Ing.
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Course content
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Topics of lectures 1. Vehicle modelling, longitudinal and transverse vehicle dynamics, kinematic and dynamic model. 2. Single track vehicle model, its applicability and limitations. Possibilities of linearization of the model. Two-track model. 3. Modelling of tyres and forces acting on the vehicle, introduction to suspension systems, static and dynamic properties of the steering system. 4. Advanced Driver Assistance Systems (ADAS) and their basic functions, an overview of sensor systems used in ADAS (Lidar, radar, camera systems, etc.) and their characteristics. 5. Analysis of lidar data for object detection and tracking. Use of camera data, lane tracking and sensor fusion. 6. Longitudinal vehicle dynamics control, automatic emergency braking, adaptive cruise control. 7. Lateral dynamics control, Lane Keeping Assist (LKA), automatic parking systems. 8. Autonomous driving, path planning, path following using predictive and linear quadratic optimal control. 9. Non-linear predictive control and its use for autonomous/semi-autonomous vehicle control. 10. Detailed analysis of the implementation of autonomous driving techniques in the open-source Apollo-Baidu autonomous car project.
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Learning activities and teaching methods
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Self-study (text study, reading, problematic tasks, practical tasks, experiments, research, written assignments), Lecture, Practicum
- Home preparation for classes
- 40 hours per semester
- Class attendance
- 40 hours per semester
- Preparation for exam
- 40 hours per semester
- Preparation for credit
- 30 hours per semester
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Learning outcomes
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The course aims to introduce students to methods of automatic control and processing of data from sensor systems that enable the vehicle to achieve partial elements of autonomous behaviour in the form of advanced driver assistance systems (ADAS, SAE levels 1,2) or higher levels of autonomy up to fully autonomous driving (SAE levels 3 to 5).
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Prerequisites
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Condition of registration: none
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Assessment methods and criteria
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Combined examination
Activity in the seminars, correct solutions to the assigned tasks, and successfully passing the tests are required to get credit. Examination is of the written and oral form (s). Understanding of the lecture topics is required.
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Recommended literature
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