The "low-prevalence effect" refers to the fact that observers often fail to detect rare targets (<5 % prevalence) during visual search tasks. Previous research has demonstrated robust prevalence effects in real-world tasks that employ static images, such as airport luggage screening. No published research has examined prevalence effects in dynamic tasks, such as driving. We conducted a driving simulator experiment to investigate whether target prevalence effects influence the detection of other vehicles while driving. The target vehicles were motorcycles and buses, with prevalence being manipulated both within and between subjects: Half of the subjects experienced a high prevalence of motorcycles with a low prevalence of buses, and half experienced a high prevalence of buses with a low prevalence of motorcycles. Consistent with our hypotheses, drivers detected high-prevalence targets faster than low-prevalence targets for both vehicle types. Overall, our results support the notion that increasing the prevalence of visual search targets makes them more salient, and consequently easier to detect.