Traffic information analysis plays an essential role in urban signalized intersection control. Wi-Fi technology can be used in multiple scenarios. It is effective to use a Wi-Fi data acquisition device to detect traffic information. This paper aims to study a traffic information detection method at a single intersection based on Wi-Fi data, determine the architecture design of the Wi-Fi data acquisition system, design the Wi-Fi data processing process, and then realize the acquisition of Wi-Fi data at a single intersection. K-means clustering algorithms and the LSTM neural network prediction model are used to obtain the space mean speed and vehicle steering ratio of the intersection sections. This method can be used to obtain and forecast various types of traffic information at intersections. The traffic information of an intersection in Xi’an is detected and predicted by using Wi-Fi technology. The experimental results show that the proposed method has high prediction accuracy.