The module aims to provide the students with a comprehensive knowledge of different types of sensors used in autonomous vehicles, their relevance for the control of advanced driving assistance systems (ADASs), and the architectures for the fusion of information coming from the plethora of sensors available. The module aims to systematically analyse industry motivations, legislations, roadmaps and customer requirements. Key parameters to critically compare different sensors are discussed, and issues related to sensor limitations and different performance are evaluated with an emphasis on system architecture and control. Topics are introduced from a practical viewpoint thus allowing the students undertaking this module to be able to critically evaluate key design parameters and independently apply the learning to a wide range of practical electronic sensors and systems deployed to achieve smart connected and autonomous vehicles.
Upon successful completion participants will be able to:
- Comprehensively understand and analyse the state of the art of automotive sensors and the control systems in ADAS/autonomous vehicles deploying them
- Critically evaluate different automotive sensors, their working principles, advantages, disadvantages, limitations and test techniques to evaluate their performance
- Interpret the role of the sensors in an advanced driving assistance system (e.g. adaptive cruise control) and independently evaluate the impact of sensors’ limitations on the system limitations
Critically compare and evaluate different strategies for sensor fusion on autonomous vehicles
Evaluate and practically represent the coverage of automotive sensors and analyse the effects of different external factors
Critically interpret and criticise up to date peer-reviewed journal papers on sensor and sensor fusion
- Introduction to sensors, their function, properties and classifications;
- Introduction to automotive sensors and their classification (general sensing, perception, virtual sensors);
- Automotive sensors: key design attributes and limitations;
- Automotive sensors: working principles and interaction with the environment;
- Role of automotive sensors in different ADASs and in autonomous vehicles;
- Introduction to actuators, their classification and their use in advanced driving assistance systems;
- ADAS architecture and control theory;
- Use of control theory in automotive electronics systems with sensors and actuators;
- Introduction to sensors fusion;
- Sensor fusion and its relationship with automotive electronic system architecture and different strategies for sensor fusion;
- Challenges related to automotive sensor fusion and connected vehicles;
- Automotive sensors and advanced driving assistance system testing: state of the art, research trends and challenges;
- Latest trends in research on sensors and sensor fusion for autonomous vehicles.
PMA : 70% of the final mark
IMA : 30% of the final mark
40 hours contact time (to include lectures, tutorials, practicals/workshops, presentations, case studies and syndicate exercises)
This module is only available on the full-time and part-time MSc Smart, Connected, and Autonomous Vehicles and as part of the part-time TAS JLR scheme.
Please note: the details of this module are correct for the current year of study and may be subject to change for future years.