Wildlife behavior when crossing roads is likely to mirror natural responses to predation risk including not responding, pausing, avoiding, or increasing speed during crossing. We generated coarse-scale behavioral predictions based on these expectations that could be assessed with GPS radiotelemetry. We evaluated our predictions using an integrated step-selection analysis of wolverine (Gulo gulo luscus) space use in relation to spatially and temporally dynamic vehicle traffic on industrial roads in northern Alberta. We compared support for alternative models of road avoidance, increased speed near roads, and road avoidance and increased speed near roads. We predicted that wolverines would avoid roads and increase their speed near roads and that these behaviors would increase with traffic volume. We found that vehicle traffic was relatively low (0 – 30 vehicles/12 hours) but important for explaining wolverine space use. Top winter and summer models indicated that wolverines avoided and increased speed near roads. Wolverine movement but not avoidance increased with traffic volume. We suggest that movement is a fine-scaled response that is more responsive to vehicle traffic than habitat selection. We show that roads, regardless of traffic volume, reduce the quality of wolverine habitats and act as barriers to movement and that higher-traffic roads might be most deleterious. We suggest that wildlife behavior near roads should be viewed as a continuum and that accurate modeling of behavior when near roads requires quantification of both movement and habitat selection. Mitigating the effects of roads on wolverines would require clustering roads, road closures, or access management.