ESR 12


SUstainable ROad MAnagement through Low Cost Techniques


I’m Ronald from Guyana! Guyana is a small developing country, in fact it is the only English speaking country in South America!
I have always had an avid Interest in Highway engineering and Transport and this is why I pursued this area in my studies. I have a BEng in Civil Engineering and a MSc in Transport Planning and Engineering. I truly believe that Transport is the key to development and building sustainable road networks can improve everyone’s lives. 
When not studying, I love running and watching sports especially football and cricket. I have managed to complete The Great North Run twice in Newcastle, UK and hope to do more runs during my studies over the next 3 years.
I am excited to embark on this SMARTI ETN journey and be part of this tremendous network of esteemed companies, universities and researchers across different cross-disciplines. I want to help contribute something that makes road networks more sustainable globally and I believe this opportunity is unique and will have a global reach to do just that.


“SuRoMa” SUstainable ROad MAnagement through Low Cost Techniques

The objective of the PhD research project consists in:

  • Developing a low-cost tool being able to ensure the best resources use for road pavement maintenance and rehabilitation. In the past few years, there has been a drastic increase in the use of Image-Based Modelling (IBM) low-cost techniques to create a high metric and visual quality, reality-based 3D models
  • The main innovative aspect lies in the use of a simple and low-cost hardware (camera or mobile phone) and software for the distresses identification and therapy
  • The other goal is to develop a new metric to evaluate the real pavement condition that does not cover traditional parameters as IRI (International Roughness Index) and Skid Resistance. Rather this metric should directly consider the actual distresses on the pavement by analysing and measuring them with the help of Artificial Intelligence tools as Fuzzy Logic, Neural Network, etc.

Following task are forecasted:

  • Review literature on road distresses, photogrammetric survey and use of Structure For Motion software
  • Advanced knowledge of camera and drone system
  • Data acquisition and analysis on road distresses through 3D modelling software
  • Implementation of interactive 3D catalogue for ready-use from the municipality of Palermo (MUNPA)

UNIPA will provide expertise with image-based modelling technique, road engineering, asset management. The partnership with strategic partners will provide:

  • ELAB: Advanced image analysis and use of drones
  • UNOTT: Theory and application of fuzzy logic, neural network and genetic algorithm
  • MUNPA: Implementation of interactive 3D catalogue for the administration of Palermo

Dr Laura Inzerillo (The University of Palermo) –