An ordered-logit model is developed to study the effects of Automated Vehicles (AVs) in the traffic mix on the average stress level of a pedestrian when crossing an urban street at mid-block. Information collected from a galvanic skin resistance sensor and virtual reality experiments are transformed into a dataset with interpretable average stress levels (low, medium, and high) and geometric, traffic, and environmental conditions. Modelling results indicate a decrease in average stress level with the increase in the percentage of AVs in the traffic mix.