The architecture of future autonomous transportation systems (ATS) is more comprehensive and complex, but there is a lack of a scientific and effective method to represent this complex architecture. A novel visualization platform based on the architecture of autonomous transportation systems is built in this paper, which can provide a clear and efficient representation of the complex architecture. This new visualization platform is driven by the data flow between systems and information flow between physical elements, and combines the

operation logic of sense-learning-decision-response to realize the dynamic simulation of ATS architecture. Finally, the validity of the theoretical approach is demonstrated with the example of "pedestrians passing a crosswalk at an unsignalized intersection with vehicles avoiding the crossing".