CogShift - Typical Trial

Files

CogShift.mp4 (230.24 MB)

Date

2023-12-11 15:47

Authors

Cecotti, Marco

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Cranfield University

Department

Type

Media

ISSN

Format

Free to read from

URI

https://dspace.lib.cranfield.ac.uk/handle/1826/22431

Citation

Cecotti, Marco (2023). CogShift - Typical Trial. Cranfield Online Research Data (CORD). Media. https://doi.org/10.17862/cranfield.rd.24787581

Abstract

This is the video of one of the vehicle trials for the CogShift project. CogShift, one of five projects which are part of an £11 million UK Government investment in autonomous vehicle research, studied driver attention and cognitive control characteristics. The project developed an optimal control-authority shifting system which takes driver attention into account. More information can be found at https://www.cranfield.ac.uk/research-projects/cogshift.

Description

Software Description

Software Language

Github

Keywords

Autonomous car', 'Driverless Cars', 'Human Factors'

DOI

10.17862/cranfield.rd.24787581

Rights

CC BY 4.0
https://creativecommons.org/licenses/by/4.0/

Relationships

Relationships

Supplements

Funder/s

TASCC: Driver-Cognition-Oriented Optimal Control Authority Shifting for Adaptive Automated Driving (CogShift)

Collections

Transport Systems