Using Formal Concept Analysis Tools in Road Environment-Type Detection

This paper presents an urban road environment-type (RET) detection algorithm for an ego-vehicle that is equipped with an automatic traffic sign recognition (TSR) system. The RETs considered in the paper are the downtown, the residential, and the business/industrial areas. The Galois-lattice (GL) often used in formal concept analysis (FCA) is employed to specify the RET detection problem in a formal manner. With the help of the GL, a correspondence between the traffic sign (TS) and crossroad (CR) categories, on the one hand, and the RETs, on the other, is established and represented. This correspondence is also characterized by means of a fuzzy matrix structure, and its alpha-cuts. After an FCA-based learning process, in the detection phase, i.e., while the ego-car is driven along the route, the maximum couplings between RETs and TS/CR sets are searched for in an on-the-fly manner. The proposed RET detection method is suitable for real-time implementation. The paper underlines the importance and applicability of GLs in classification problems.