Speech-based command interfaces are becoming more and more common in cars. Applications include automatic dialog systems for hands-free phone calls as well as more advanced features such as navigation systems. However, interferences, such as speech from the codriver, can significantly hamper the performance of the speech recognition component, which is crucial for those applications. This issue can be addressed with {\em adaptive} interference cancellation techniques such as the Generalized Sidelobe Canceller (GSC). In order to cancel the interference (codriver) while not cancelling the target (driver), adaptation must happen only when the interference is active and dominant. This paper proposes a novel approach for pre-estimation of target and interference energies, along with its application to explicit'' adaptation control: a hard decision whether the filter(s) should be updated or not. It is compared with an implicit'' adaptation control method that does not require such pre-estimation. Experiments on real in-car recordings validate both approaches.