<p>Curved streets have long played a crucial role in shaping the experience of urban space, affecting the visual perception and psychological expectations of pedestrians. This study examines how key geometric variables, such as curvature, wall spacing, and segmentation, affect spatial expectations in curved environments. To carry out the study in a real setting, a field survey of 78 curved-street cases in 14 countries was first conducted to extract representative spatial configurations as reference types. These are then abstracted into 3D computer graphics (3DCG) simulation models, which enable us to control the manipulation of geometric parameters while eliminating non-visual variables such as color and texture. A total of 223 participants, including professionals, students in design-related fields, and laypeople, took part in a perception-based experiment evaluating maximum desired position and desired intensity. Our setting is that participants have not actually visited these locations. The simulated environment captures universal spatial characteristics, focuses on universal perception mechanisms, and reduces the familiarity of specific locations to record the first intuitive feelings of participants. Multiple regression analyses were used to quantify the relationship between physical street attributes and psychological responses. The results show that streets with moderate curvature and well-spaced building elements enhance spatial depth and continuity, thus enhancing the sense of expectation. Based on the above, we construct a prediction model to link geometric street features with perceived outcomes. Through empirical observation, virtual simulation, and statistical analysis, this study provides a new perspective on how spatial morphology affects human cognition. These findings can contribute both theoretically and practically to the development of more attractive, psychologically resonant, and human-centered urban public Spaces.</p>