ADEPT: AI-Based Driving Evaluation and Performance Testing

The Industry and Innovation Research Institute (I2Ri) draws on talents, expertise and facilities across Sheffield Hallam University. The vision is to be the leading provider of applied research excellence delivering materials, computing, science and engineering innovations meeting the development needs of industry.

This project is part of a Graduate Teaching Assistants scheme, in which the successful applicant will undertake certain teaching duties associated with the student experience, in addition to working towards a PhD qualification. They will contribute up to 180 hours of support for research or teaching related activity per academic year. This activity forms part of the scholarship award and there is no additional payment.

PhD Research Topic

The aim is to develop an artificial intelligence (AI) based platform that can effectively integrate the data regarding learner-driver’s behaviour, real-time road conditions, and vehicle-related actions, and generate accurate driving evaluation reports according to UK driving standards. This prototype will undergo rigorous evaluation to ensure its effectiveness and reliability in automated driving testing and training scenarios. The study focuses on the design, development, evaluation of an AI-powered platform to automate drivers’ training and driving testing procedure.

Human-conducted driving tests often lack standardization, resulting in subjective assessments vulnerable to biases and errors, leading to dissatisfaction among candidates. This issue not only wastes time and resources but also induces stress and anxiety in individuals due to repeated failures and delayed evaluation. Moreover, human-driven training is expensive and inefficient, further inflating costs. However, these challenges present an opportunity for innovation. This research aims to address these issues by developing an AI-based automated platform for driving tests and training, which enhances objectivity and precision while reducing expenses.

The proposed platform will integrate data regarding learner-drivers' behaviour, real-time road conditions, and vehicle-related information to generate accurate reports according to UK driving standards. Leveraging advancements in AI-driven image processing and autonomous driving technology, the platform will consolidate critical aspects of driver behaviour, real-time road conditions, and vehicle actions. This integrated system will strive to produce precise reports aligning with the stringent standards governing driving practices in the UK.

The platform will utilize real-time data extracted from the road and its surroundings to determine appropriate actions, monitoring the driver's behaviour and actions such as indicator usage before lane changes or turns. By generating an expected plan based on autonomous driving principles and contrasting it with the driver's actions, the platform will provide comprehensive reports on whether the driver executed the requisite actions at designated junctures.

This doctoral project, based in the department of computing, offers candidates the opportunity to gain deep understanding of computer vision, IoT, and system integration. Highly motivated candidates with backgrounds in computer science, software engineering, or related fields are encouraged to apply. Rigorous evaluation of the prototype's efficacy and dependability, particularly in the context of automated driving testing and training scenarios, will be a central focus of this research.

Eligibility

Applicants should hold at least a 1st or 2:1 Honours degree in Biomedical Science, Computing, Statistics or a related discipline. An MSc qualification in a related area is desirable. 

We strongly encourage applications from individuals from groups underrepresented in postgraduate research, including but not limited to women, LGBTQ+, and minoritised ethnic groups. This in particular includes support for Black and Asian ethnic minority British students. Home students from minority groups will be fast-tracked to interview.

Information for International applicants

English language requirements of IELTS 7 with a minimum score of 6.5 in all test areas (or equivalent) are mandatory if English is not your first language. Qualifications should have been taken within the last two years.  Further information can be found here.

How to apply

To apply for this GTA scholarship, please use our online application form.

You must ensure that you upload:

1. A personal statement (1 page maximum) detailing your interest in the project and how your experience in academia, industry, research or social activities makes you the best candidate (Please upload this in place of a proposal). We’re looking for evidence of:

• motivation and curiosity for postgraduate research
• analytical and technical expertise related to the research proposal
• ability to communicate clearly
• planning and organisational skills
• ability to work independently and collaborate with others
• commitment to integrity and responsible research
• resilience to setbacks and challenges
• where you might contribute to teaching

2. Two letters of reference, at least one from an academic and both dated within the last 2 years (if unable to provide please include referee details).

3. Copy of your highest degree certificate

4. Non-UK applicants must submit IELTs results (or equivalent) taken in the last two years and a copy of their passport.

Application deadline: 10 May 2024

Interviews: 3 June 2024 onwards

Information about our research degrees can be found here.

Overview of GTA scheme

The Conditions of Award