Automatic linguistic reporting in driving simulation environments

Linguistic data summarization targets the description of patterns emerging in data by means of linguistic expressions. Just as human beings do, computers can use natural language to represent and fuse heterogeneous data in a multi criteria decision making environment. Linguistic data description is particularly well suited for applications in which there is a necessity of understanding data at different levels of expertise or human-computer interaction is involved. In this paper, an application for the linguistic descriptions of driving activity in a simulation environment has been developed. In order to ensure safe driving practices, all new onboard devices in transportation systems need to be evaluated. Work performed in this application paper will be used for the automatic evaluation of onboard devices. Based on Fuzzy Logic, and as a contribution to Computational Theory of Perceptions, the proposed solution is part of our research on granular linguistic models of phenomena. The application generates a set of valid sentences describing the quality of driving. Then a relevancy analysis is performed in order to compile the most representative and suitable statements in a final report. Real time-series data from a vehicle simulator have been used to evaluate the performance of the presented application in the framework of a real project.