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Details of Grant 

EPSRC Reference: EP/R037795/1
Title: iSeat - Towards an intelligent driver seat for autonomous cars
Principal Investigator: Anvari, Dr B
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Department: Civil Environmental and Geomatic Eng
Organisation: UCL
Scheme: Standard Research - NR1
Starts: 01 July 2018 Ends: 31 October 2020 Value (£): 251,453
EPSRC Research Topic Classifications:
Computer Sys. & Architecture
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
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Summary on Grant Application Form
According to the most optimistic predictions, the first commercially available fully-autonomous cars are expected in 2040 offering the consumer a full end-to-end journey. These self-driving vehicles will be equipped with technology allowing autonomy Level 5 in which there is no interference required by the human. The concept of autonomy levels was first published by the international Society of Automotive Engineers in 2014. The report defines six levels of autonomy that automakers would need to achieve on their way to building the no-steering-wheel self-driving bubble pods of the future reaching from the fully-manual Level 0 to the fully-autonomous Level 5.

In the race towards the first commercially available fully-autonomous car, the majority of cars on UK roads will be equipped with technology that allows Level 3 or 4 autonomy over the next two decades. Drivers will be provided with increasingly sophisticated features such as lane-keep and steering assist. These semi-autonomous cars might be able to transport the driver autonomously on sections of a journey. However, the driver is required to take control occasionally between different levels of autonomy when required to complete an end-to-end journey. These transitions between autonomy levels cause safety concerns, as the driver might not be fully aware of the surrounding situation and the enabled autonomy features instantly.

This project proposes a new interface design for semi-autonomous cars called iSeat. This system is fundamentally different compared to current systems (such as Tesla's Autopilot or DistronicPlus by Mercedes) using visual or auditory indications which might be mentally overloading and distracting for the driver. iSeat is an intelligent driver seat acting as a co-pilot measuring the current mental and physical engagement of the driver and allowing safe, coordinated and timely transitions between different levels of autonomy. Of particular significance is the driver seat made of robotic structures serving the feedback purpose as well as providing monitoring capabilities through direct contact with the human during any level of autonomy: Tactile sensation can be fed back to the driver, the seat ergonomics and comfort can be changed and the robotic structures can measure the pressure distribution of the driver's weight. iSeat sensing information will be fused with multi-modal sensing data from electrical activity produced by skeletal muscles (Electromyography (EMG) signals) and in the driver's brain (Electroencephalography (EEG) signals), and input from vision cameras regarding the driver's posture and the point of gaze (i.e. where the driver is looking). This real-time knowledge will be classified through machine learning and affective interaction techniques in terms of the awareness state of the driver. Personalised feedback will be provided (i.e. tactile sensation, stiffness feedback, change of the driver seat ergonomics/comfort, visual/auditory feedback) to support the driver so that safe, timely, effective and intuitive transitions between different autonomy levels can be completed.

The iSeat system builds upon a complete re-think of the manner in which humans interact with autonomous cars. The smart combination of sensor systems, machine learning, affective computing, human factors, haptics and robotics will result in a bi-directional human-machine cooperation that is safe, intuitive, effective, and personalised.
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