Introductory description

The automotive sensors and sensor fusion module analyses the main working principles and limitations of automotive sensors, particularly focusing on perception sensors and their relationship with assisted and automated driving functions. The role of sensor modelling and testing is highlighted through all the module, with real case studies and tutorials. Moreover, the module explains what are the main advantages and challenges when combining and fusing the data from different sensor technologies.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

• 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.

Learning outcomes

By the end of the module, students should be able to:

• Comprehensively understand and analyse the state of the art of automotive sensors 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

Indicative reading list

• KALA, Rahul. On-road Intelligent Vehicles: Motion Planning for Intelligent Transportation Systems. Butterworth-Heinemann, 2016. (ISBN: 0128037563)
• ESKANDARIAN, Azim (ed.). Handbook of intelligent vehicles. Springer, 2014. (DOI: https://doi.org/10.1007/978-0-85729-085-4)
• WATSON, Joseph. Automotive sensors. Momentum Press, 2009. (ISBN: 1-60650-011-2)
• TERZIS, Anestis (ed.). Handbook of camera monitor systems: The automotive mirror-replacement technology based on ISO 16505. Springer, 2016. (DOI: https://doi.org/10.1007/978-3-319-29611-1)
• QU, Zhihua. Cooperative control of dynamical systems: applications to autonomous vehicles. Springer Science & Business Media, 2009. (DOI: https://doi.org/10.1007/978-1-84882-325-9)
• FOSSEN, Thor I.; PETTERSEN, Kristin Y.; NIJMEIJER, Henk (ed.). Sensing and Control for Autonomous Vehicles: Applications to Land, Water and Air Vehicles. Springer, 2017. (DOI: https://doi.org/10.1007/978-3-319-55372-6)
• REIF, Konrad. Automotive Mechatronics. Springer Fachmedien Wiesbaden, 2014. (DOI: https://doi.org/10.1007/978-3-658-03975-2)
• JAIN, Vipul; HEYDARI, Payam. Automotive Radar Sensors in Silicon Technologies. Springer Science & Business Media, 2012. (DOI: https://doi.org/10.1007/978-1-4419-6775-6)
  A variety of up-to-date sources including:
• Latest government / UK Automotive Council roadmaps for autonomous vehicles
• Latest automotive legislation and standards
• Current academic research in the field of smart connected autonomous vehicles

View reading list on Talis Aspire

Subject specific skills

Sensor metrics; automotive sensor performance; automotive sensor classification; automotive sensor basic principles, limitations, strengths; automotive sensor models; automotive sensor fusion.

Transferable skills

Team work; Work effectively in a group or team to achieve goals; Personal Motivation, Organisation and Time Management skills; Research and Analytical Skills; presentation skills; Oral and written communication skills.