(LSTM)layers for identifying short-term and long-term dependencies.Our approach may utilize the heterogeneous spatiotemporal correlation features of the traffic flowdataset to deliver better performance traffic flow prediction than existing deep learning models.The research findings show that adding spatio...
This dataset is provided by Hanzhou Jiaotong & Amap. KDD CUP 2017: https://tianchi.aliyun.com/competition/entrance/231597/information 数据列表 数据名称上传日期大小下载 dataSets.zip2018-04-038.50MB dataSet_phase2.zip2018-04-031.36MB 文档
TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning Preliminary 此文提出了一个交通流预测方向可以进的新坑。大概意思就是现实世界中的路网每隔一段时间就会发生变化,当路网中加入新的传感器时应该如何快速的更新线上已经部署好的交通流预测模型呢?此...
With the rapid growth of traffic sensors deployed, a massive amount of traffic flow data are collected, revealing the long-term evolution of traffic flows and the gradual expansion of traffic networks. How to accurately forecasting these traffic flow attracts the attention of researchers as it is ...
The data mainly consists of three traffic parameters, including flow, average speed, and average density. We treat 307 detection points as 307 road segments and construct the link relationship according to the road network topology. The experimental dataset is divided into training sets, validation ...
“Datasets used” section, the whole dataset is defined through six classes. In order to increase features of datasets such that better results are obtained data preprocessing and augmentation is used. These addresses various issues which can be present in images such as noise, inconsistency and ...
convolutional backbone network. Experimental results on the real-world dataset show that our strategy enhances the forecasting performances of backbones at various prediction horizons. The ablation and perturbation analysis further verify the effectiveness and robustness of the proposed method. To the best...
Organize some grid-based traffic flow datasets, mainly New York City bicycle and taxi data traffic dataset data-collection traffic-data spatio-temporal-data traffic-prediction grid-data traffic-flow nyc-taxi-dataset nyc-taxi nyc-bike tdrive traffic-dataset taxibj Updated Jun 30, 2021 City...
dataset to store the data for every vehicle in a generic vehicle object. This way of working ensures that the dataset itself is used in its original format such that all original documentation can be used and other scripts based on that documentation will still work. But TraViA uses the same...
deep-learning toolkit traffic eta map-matching representation-learning on-demand-service spatio-temporal traffic-prediction trajectory-prediction time-series-prediction spatio-temporal-prediction traffic-flow-prediction pytorch-implementation od-matrix traffic-forecasting estimated-time-of-arrival traffic-accident-...