Traffic Impact Evaluation Method for Urban Large-Scale Activities Based on Multi-Source Data

Large-scale activities usually put heavy pressure on urban transportation systems. The research constructs an evaluation index system from three dimensions: time, space, and degree of impact on traffic operation in the surrounding areas of venues. The index values are calculated based on bus IC card data, subway AFC data, urban road detector data, taxi meter data, and GPS data. Maximizing deviation is used to assign a weight to the evaluation index and the traffic impact index of urban large-scale activities is obtained by weighting calculation. Finally, the research uses the K-means clustering method to grade the traffic impact degree of urban large-scale activities. The research takes the large-scale activities held in Beijing workers’ stadium in recent years as an example to verify. Results show that the method proposed in the article has good applicability and can clearly distinguish the impact degree of large-scale activities on traffic operation.