Traffic state data imputation: An efficient generating method based on the graph aggregator

Authors: Xu Dongwei, Peng Hang, Wei Chenchen, Shang Xuetian, Li Haijian

Paper:Xu, Dongwei, et al. "Traffic State Data Imputation: An Efficient Generating Method Based on the Graph Aggregator." IEEE Transactions on Intelligent Transportation Systems (2021).

Paper Link: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9582618

This paper presents GA-GAN (Graph Aggregate Generative Adversarial Network), consisting of graph sample and aggregate (GraphSAGE) and a generative adversarial network (GAN), to impute missing road traffic state data.

Requirements

• python3.7
• tenforflow1.14.0
• numpy
• pandas
• matplotlib

Data Preparation

Two real-world large-scale traffic speed datasets were used as case studies. PEMS-BAY and Seattle dataset can be downloaded from here.
链接：https://pan.baidu.com/s/1gOPuaNTOE-PTVYMluREsLQ 提取码：xeew