Predicting the Getting-on and Getting-off Points Based on the Traffic Big Data

Taxi is an important part of urban passenger transportation. Taxi traffic big data has become an important research topic in smart transportation cities. In order to dispatch taxi resources more reasonably, this paper based on the GPS big data of Baota District of Yan’an City, predicting the getting-on point and getting-off point. Firstly, the historical data is cleaned, and then the DBSCAN clustering algorithm is used to divide the area with sufficient high density into several clusters. Finally, the high-definition map API is used to visualize the prediction results, which solves the problem of forecasting the taxi loading point. In real life, it has a practical reference value for the travel of local residents.