Camera-based lane border detection in arbitrarily structured environments

In this paper we present a new approach for monocular image based lane border detection in situations where the characteristics of the pavement and the lane border are unknown. To achieve real time performance on standard hardware we analyze statistical characteristics of 1D signals on certain profile lines to find different types of features which belong to the lane border. These features are used for fitting a border model in. The proposed method shows good results in complex situations. It was evaluated in different scenarios with cobblestone pavement, lowered curbs, lane markers, parking cars defining the lane border as well as disturbances on the road like shadows, dirt and asphalt damages. The method was successfully used within the Volkswagen research vehicle `eT' (electronic Transporter).

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