Optimization of automotive color filter arrays for traffic light color separation

Abstract

Traffic light (TL) classification is an important feature for automated driving, and it requires correct color separation of the TL signals captured using cameras. A key camera component for the color separation performance is the color filter array (CFA). For common automotive-specific CFAs, we have observed unsatisfactory performance for TL color separation, which indicates the need for an optimization. Based on typical scenarios for TL classification and a set of recorded TL signals, we evaluate the performance of common automotive CFAs. For a quantitative evaluation, we propose a suitable color distance metric. We also propose a method for optimization of the CFA and show that using this method, reference color separation performance can be achieved, trading in only a small amount of sensitivity.