Driving simulation has become an important research tool in a wide array of fields; but the application of research findings often hinges on simulator validation and fidelity. However, simulator validation studies frequently indicate relative differences in driver behavior. The research team hypothesized that these differences may be influenced by differences in drivers’ perception of simulated versus on-road environments. The objective of this study was therefore to identify the ranges of perceived complexity that can be achieved in simulated roadways as compared to on-road environments. Also presented is a descriptive model of perceived complexity followed by a presentation of potential applications of this model, including a proposed methodology for predicting roadway complexity. Participants saw several repetitions of on-road and simulated roadways, and were asked to rate the complexity using two questions: one asking about task complexity, and the other asking about visual complexity. Results indicated that the achievable range of complexity is consistent across simulated and on-road environments, and illustrated the descriptive power of the beta distribution in describing perceived complexity for roadways. Applying the proposed methodology may allow for the development of simulator experimental scenario designs that are equivalent with respect to driver perception, rather than scenarios that are only technically and visually replicated across simulated and on-road environments.