Advanced driver assistance systems (ADAS) need to account for the driver’s awareness of the environment to be effectively used. This study examines the impact of environmental features (eg, visual complexity, object density, roadway type, lighting) on drivers’ situation awareness (SA). This is achieved using a controlled study with 40 participants. Using a split-plot design, the participants were shown 30 out of 75 real-world driving scenarios displayed in a driving simulator environment. Participants’ responses to Situational Awareness Global Assessment Technique (SAGAT) queries on the type and coordinates of objects in the scene were used to calculate SA scores. A hurdle model was developed to estimate participants’ SA scores. The key findings highlight visual complexity as a significant predictor of SA scores. This predictor was easy to compute and able to capture the complexity of objects that impact road safety as well as the visual clutter in the background. The model showed that drivers were able to identify at least one object of interest in complex environments with high visual complexity and with many objects. A higher proportion of vulnerable road users was associated with a greater likelihood of a non-zero SA score, but the SA score was lower compared to environments with higher proportions of cars. The findings of this study provide insights into the environmental factors to be considered for SA predictive models.