Road condition is a broad term that incorporates everything from imperfections like potholes and
cracks to the random deviations that exist in the road surface. To build an image of the road condition,
road irregularities need to be measured first. Existing methods of gauging the roughness are based
either on visual inspections or using one of a limited number of instrumented vehicles that can take
physical measurements of the road irregularities. And this is how the road authority in the Netherlands,
Rijkswaterstaat (RWS) does it nowadays. RWS is a participant in the Smart In-Car project
and the overall goal of the project is to improve traffic flow and increase traffic safety by using more
advanced sensor-, control and information/communication systems.
In the Smart-In-Car project, a pilot was started and eventually 200 to 300 cars will be equipped with a
module that can access the data of the vehicle’s CAN-bus, called uCAN. In addition data such as GPS
position and three-axes accelerations will be provided. One of the things that interests RWS is whether to conduct a feasibility study at the possibility of obtaining an indication of the road quality with this uCAN data.
This report shows the feasibility to accurately classify road profiles using axle and body accelerations
from a range of simulated vehicle-road dynamic scenarios with uCAN data.
Traineeship report. - DC 2012.056