This study focuses on the main urban area of Yangzhou City and conducts a quantitative comparative analysis of traffic accessibility during normal weather and extreme precipitation conditions (typhoon) based on GPS trajectories of buses. From both temporal and spatial dimensions, it comprehensively examines the impact of extreme precipitation on bus travel speed, travel time, and the commuting range of residents in the main urban area of Yangzhou City. (1) Through the mining and analysis of multi-source heterogeneous big data (bus GPS trajectory data, bus network data, rainfall remote sensing data, and road network data), it is found that the rainstorm weather greatly affects the average speed and travel time of buses. In addition, when the intensity of heavy rainfall increases (decreases), the average bus speed and travel time exhibit varying degrees of spatio-temporal change. During the morning and evening rush hour commuting period of rainstorm weather, there are obvious differences in the accessibility change in each typical traffic community in the main urban area of Yangzhou city. In total, 90% of the overall accessibility change value is concentrated around −5 min~5 min, and the change range is concentrated around −25~10%. (2) To extract the four primary traffic districts (Lotus Pond, Slender West Lake, Jinghua City, and Wanda Plaza), we collected Points of Interest (POI) data from Amap and Baidu heat map, and a combination analysis of the employment–residence ratio model and proximity methods was employed. The result show that the rainstorm weather superimposed on the morning peak hour has different degrees of impact on the average speed of the above-mentioned traffic zones, with the most obvious impact on the Lotus Pond and the smallest impact on Wanda Plaza. Under the rainstorm weather, the traffic commute in the main urban area of Yangzhou in the morning and evening peak hour is basically normal. The results of this paper can help to quantify the impact of typhoon-rainstorm weather events on traffic commuting in order to provide a scientific basis for the traffic management department to effectively prevent traffic jams, ensure the reliability of the road network, and allow the traffic management department to more effectively manage urban traffic.