How can an autonomous vehicle decide safely if a pedestrian will cross the road?
Pedestrians and cyclists often use gaze behaviour and body language to indicate their movements to vehicles with human drivers but how will autonomous vehicles decide if a pedestrian is about to enter the road? This study will develop and apply AI and computer vision methods combined with posture and behaviour analysis to dynamically analyse pedestrian behaviour to improve the functionality and safety of autonomous vehicles. It will apply new methods to a large set of naturalistic driving data of the operations of vehicles in a large range of normal driving conditions.
Entry requirements: Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in:
Artifical intelligence methods
All students must also meet the minimum English Language requirements: https://www.lboro.ac.uk/international/apply/english-language-requirements/.
A relevant Master's degree and / or experience in one or more of the following will be an advantage: Computer vision or artificial intelligence
How to apply: All applications are made online, please select the school/department name under the programme name section and include the quote reference number:
Programme name: Loughborough Design School EngD
Reference: LDS/July 19/UFPDT3
This is an open call for candidates who are sponsored or who have their own funding. If you do not have funding, you may still apply, however Institutional funding is not guaranteed. Outstanding candidates (UK/EU/International) without funding will be considered for funding opportunities which may become available in the School.