Road scene monotony detection in a fatigue management driver assistance system

Automated fatigue detection devices show much promise in combating fatigue related accidents. One aspect which hampers the introduction of these technologies is context awareness. In this paper we develop and evaluate a road scene monotony detector. The detector can be used to give context awareness to fatigue detection tools to minimise false positives. The approach could also be used by road makers to quantify monotony on fatigue prone stretches of road. The detector uses MPEG compression to measure the change in information content of the road scene over time. We show that the detector correlates highly with human identified monotonous scenes. The technique is consistent over time and applicable for day and night operation. The compression is augmented with lane tracking data to distinguish between otherwise difficult cases. The detector is integrated into a fatigue management driver assistance system.

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