This thesis develops and tests an empirical method to quantifying drivers’ level of acceptance for alerts issued by automotive active safety systems. The method uses drivers’ subjective level of acceptance for alerts that are literally false alarms as a measure to guide the development of alerting criteria that can be used by active safety systems. Design for driver acceptance aims at developing systems that overcome drivers’ dislike for false alarms by issuing alerts only when drivers finds them reasonable and therefore are likely to accept them. The method attempts to bridge the gap between field experiments with a high level of ecological validity and lab based experiments with a high level of experimental control. By presenting subjects with video recordings of field data (e.g., traffic incidents and other situations of interest), the method retains high levels of both experimental control and ecological validity.

This thesis first develops the theoretical arguments for the view that false alarms are not only unavoidable, but also that some false alarms are actually useful and, hence, desirable as they provide useful information that can be used (by the proposed method) to assess driver acceptance of active safety systems. The second part of this thesis consists of a  series of empirical studies that demonstrates the application of the assessment method. The three empirical studies showed that drivers’ subjective level of acceptance for alerts that are literally false alarms are a useful measure that can guide system designers in defining activation criteria for active safety systems. The method used to collect the driver’s subjective acceptance levels has also been shown to produce reliable and reproducible data that align with the view of the drivers who experienced the situations in the field. By eliciting responses from a large number of observers, we leverage the high cost of field data and generate sample sizes that are amenable to statistical tests of significance.