Doctoral theses of the School of Engineering at Aaltodoc (external link)
Doctoral theses of the School of Engineering are available in the open access repository maintained by Aalto, Aaltodoc.
Public defence, geoinformatics, MSc (Tech) Aimad El Issaoui
A vehicle-mounted laser scanner allows road ruts and defects to be measured with very high accuracy while driving. Public defence from the Aalto University School of Engineering, Department of Built Environment.
In this event, we are committed to Aalto University’s principles for a safer space.
Title of the thesis: Automated pavement distress detection and quantification with multi-platform laser scanning
Thesis defender: Aimad El Issaoui
Opponent: Professor, DSc Stephan Nebiker, University of Applied Sciences and Arts Northwestern, Switzerland
Custos: Matti Vaaja, Aalto University School of Engineering, Department of Built Enviroment
A vehicle-mounted laser scanner allows road ruts and defects to be measured with very high accuracy while driving.
Roads deteriorate constantly under traffic, studded tyres and harsh weather. Ruts, cracks and potholes reduce traffic safety and let water into the road structure, which speeds up further damage. Today, road condition is still largely assessed with dedicated survey vehicles and visual inspection, which is slow, expensive and partly inaccurate. In Finland alone, the road repair backlog amounts to billions of euros.
This doctoral research investigated whether pavement damage can be measured automatically from a car driving at normal speed using laser scanning. A laser scanner produces an accurate three-dimensional point cloud of the road surface, from which computer algorithms identify ruts, cracks and other defects and calculate their depth, area and volume. The accuracy of the methods was verified against high-precision reference measurements.
The results showed that a car-mounted survey grade laser scanner measures rut depth with roughly millimetre accuracy, which is well sufficient for road maintenance, as repairs are typically triggered only when ruts exceed 15 millimetres. A new detection algorithm developed in the thesis, combining three complementary methods, found pavement defects reliably. The research also demonstrated, for the first time, that the perception sensors of autonomous cars can measure road ruts with useful accuracy.
Based on the results, a single survey drive could in the future replace several separate road condition measurements, since the same data reveal ruts and defects while also producing a three-dimensional model of the entire road environment. As autonomous and sensor-equipped cars become more common, road condition could be monitored continuously as part of normal traffic, without dedicated survey vehicles. This would allow damage to be detected early, repairs to be targeted correctly, and maintenance budgets to be used more effectively on ageing road networks.
Key words: laser scanning, road maintenance, pavement distress, rutting, point cloud, autonomous vehicles, mobile mapping
Thesis available for public display 7 days prior to the defence at Aalto University's public display page.
Contact information: Aimad El Issaoui, aimad.elissaoui@maanmittauslaitos.fi
Doctoral theses of the School of Engineering
