EPSRC Reference: |
EP/N012089/1 |
Title: |
TASCC: Driver-Cognition-Oriented Optimal Control Authority Shifting for Adaptive Automated Driving (CogShift) |
Principal Investigator: |
Brighton, Professor JL |
Other Investigators: |
|
Researcher Co-Investigators: |
|
Project Partners: |
|
Department: |
Sch of Aerospace, Transport & Manufact |
Organisation: |
Cranfield University |
Scheme: |
Standard Research - NR1 |
Starts: |
15 December 2015 |
Ends: |
14 December 2019 |
Value (£): |
1,587,193
|
EPSRC Research Topic Classifications: |
Human-Computer Interactions |
Robotics & Autonomy |
|
EPSRC Industrial Sector Classifications: |
Transport Systems and Vehicles |
|
|
Related Grants: |
|
Panel History: |
|
Summary on Grant Application Form |
The emerging development of automated driving demands a mutual understanding and a smooth coordination between human driver and vehicle controller, so as to avoid conflict and mismatch in demands, and instead achieve desirable driving performance, smooth and swift transitions which enhance driving safety during complex operating scenarios. However, such driver-vehicle collaboration during automated driving will impact on the driver's attention and cognition and it is important to consider these effects in order to prevent any negative impact on driving. This project aims to achieve a safe engagement and smooth and swift control-authority shift between the driver and the vehicle controller during adaptive automated driving. To this aim, we will first conduct a comprehensive study of driver attention and cognitive control characteristics when interacting with the vehicle controller. An optimal control authority shifting system which considers driver cognition will then be systematically developed and validated. This cross-disciplinary research challenge will be addressed using a unique combination of researchers from engineering, cognitive neuroscience and human factors. The research will not only contribute to the cutting-edge technology innovations in automated driving, but will also result in a major advance in the science of human attention and cognitive control when interacting with automation.
|
Key Findings |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
Potential use in non-academic contexts |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
Impacts |
Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
Summary |
|
Date Materialised |
|
|
Sectors submitted by the Researcher |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
|
Project URL: |
|
Further Information: |
|
Organisation Website: |
http://www.cranfield.ac.uk |