The Road eye sensor is an optical sensor for road condition classification on vehicles. The sensor consists of three laser diodes and a photo detector. As different phases of water (wet, ice and snow) reflect light differently due to absorption and scattering it is possible to draw conclusions from the Road eye measurements regarding road conditions and the surface roughness.
Classification of different road conditions is mainly based on the differences in absorption between the three wavelengths. The surface roughness is mainly based on the changes of intensity levels for one wavelength, respectively. Within CASTT there is two different projects where the sensor is utilized:
The aim of the project is to use the Road eye to characterize winter road conditions in terms of surface material and structure that can be used by the automotive and automobile test companiesto increase the repeatability in vehicle testing.
The aim of the project is to use the Road eye to characterize winter road conditions and use this as feedback to road condition forecasts to investigate the possibility to improve road weather and condition forecasts.
For vehicle testing repeatability is important, as a lot of vehicle testing is carried out outdoors the weather will play a part in the conditions of the testing. By classifying the road condition during the test it is possible to get a better picture of how the weather condition has affected the tests.
For road weather and condition forecasts it is important to map the road conditions to a position to get a good image on where slippery road conditions appear.
Video of logged and positioned road condition data. Red=ice, yellow=snow, blue=wet asphalt and black=dry asphalt.
For real time data go to: sm-pc777.sm.ltu.se/roadeye
Project leader: Johan Casselgren