Intelligent Vehicular Ad-hoc Networks (VANET) (Ref: CO/LG-SF1/2026)

About the Project

Vehicular Ad-hoc Network (VANET) is an emerging research area and has been attracting great attention in recent years. VANET is a special case of MANET (Mobile Ad hoc Network) and is a key part of Intelligent Transportation System (ITS) framework.

Nowadays, Vehicle-to-everything (V2X) communication in VANET has emerged as a crucial component in both advanced ITS and Internet of Things (IoT) for information transmission and vehicular communication. Due to the rapid growth of V2X technologies, a plethora of safety-aware and non-safety-aware applications have emerged, such as collision avoidance (e.g., pre-collision warning), traffic sign notification (e.g., curve speed warning), traffic management (e.g., intelligent traffic control), traffic monitoring (e.g., vehicle tracking), intervehicular entertainment, etc.

The project will work on an open-source platform. Novel intelligent algorithms would be expected to be developed in VANET caching or VANE routing or VANET congestion control area (one subject area would be sufficient) and compare to benchmarks. This project will have great potential to work with industrial collaborator national highway.

Please contact Dr. Guan (L.Guan@lboro.ac.uk) to make any project enquires.

Name of primary supervisor/CDT lead:

Dr. Lin Guan L.Guan@lboro.ac.uk

https://www.lboro.ac.uk/departments/compsci/staff/lin-guan/

Entry requirements:

A minimum 2:1 BSc honours degree or MSc (or equivalent international qualification) in a Computer Science related degree.

English language requirements:

Applicants must meet the minimum English language requirements. Further details are available on the International website (http://www.lboro.ac.uk/international/applicants/english/).

Bench fees required: No

Closing date of advert: 1st October 2026

Start date: February 2027

Full-time/part-time availability: Full-time 3 years

Fee band: 2025/26 Band RB (UK £5,006, International £28,600)

How to apply:

All applications should be made online. Under programme name, select Computer Science. Please quote the advertised reference number: CO/LG-SF1/2026 in your application.

To avoid delays in processing your application, please ensure that you submit a CV and the minimum supporting documents.

The following selection criteria will be used by academic schools to help them make a decision on your application.

Please note that this criteria is used for both funded and self-funded projects. Please note, applications for this project are considered on an ongoing basis once submitted and the project may be withdrawn prior to the application deadline, if a suitable candidate is chosen for the project.

Project search terms:

Computer science, AI, Machine Learning, Intelligent, Networks and Systems, Intelligent transportation systems (ITS), Optimisation, Prediction, Vehicular Ad-hoc Networks (VANET)