Project code



School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the school of computing and will be supervised by Dr Gelayol Golcarenarenji, Dr Farzad Arabikhan, Dr Rahim Taheri and Dr Alexander Gegov.

The work on this project could involve:

  • Design and prototype a vision-based pipeline for the effective detection of on-road Obstacles in real time based on the attention-based CNN methods to decrease false-negative and false-positive rates and improve accuracy.
  • Fusion of optical imagery and lidar cloud points to provide more accuracy.
  • Develop the proposed algorithms on low-powered computers (e.g., Jetson AGX Orin) on the edge to increase data security and privacy.


Autonomous Vehicle (AV) is a promising way of robust, secure, and low-carbon transportation. Real-time accurate obstacle detection is of paramount importance. 

In Avs to avoid the collision. However, due to the complex real-time scenarios, robust obstacle detection is still a major challenge in Avs. These challenges have a detrimental effect on accuracy and performance and should be taken into consideration in AV applications. Optical images and LiDAR data have unique characteristics that make them suitable in various applications. Fusing these two data types causes the disadvantage of one being compensated by an advantage of the other and thereby makes the detection systems more robust.

Hence, the aim of this project is to design and develop a novel real-time portable cost-effective vision-based obstacle detection system with high-accuracy suitable for Autonomous vehicles.



Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (conditions apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.


You should have computer programming knowledge using R or Python.


How to apply

We’d encourage you to contact Dr Gelayol Golcarenarenji ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.

When applying please quote project code: COMP6351025