Mahalanobis distance-based road condition estimation method using network-connected manual wheelchair

This paper describes a method to estimate road condition using our developed network-connected manual wheelchair. We have been developing the wheelchair on which torque sensors, an accelerometer and a GPS receiver are implemented, for gathering the road condition data onto our server PC. Our final purpose is to develop a system which display traffic disturbances for manual wheelchairs on the digital map automatically. For this purpose, this study aims to associate the sensor values with road conditions using Mahalanobis distance. In this paper, firstly, our developed wheelchair is explained briefly. Then, characteristics of acquired data is shown. After that, definition of unit space for this problem and calculation of Maharanobis distance are described. Finally, possibility of categorizing road conditions using the Maharanobis distance defined by significance level is explained in detail with the experimental data.