This paper introduces a long-term traffic flow dataset at an intra-city scale with high spatio-temporal granularity. The dataset covers the Glasgow City Council area for four consecutive years spanning the COVID-19 pandemic, from October 2019 to September 2023, providing comprehensive temporal and ...
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 of our knowledge, this is ...
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 Overview Highway tollgates are well known bottlenecks in t...
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...
In this step, how to choose a suitable training fashion and the dataset are also big challenges. On-line and Off-line training are the two popular options for the training stage, and also whether using real-time or historical data source needs to be considered. In fact, the training ...
Fig. 15. ANN-PSO training response of the best performance of long and short trucks traffic dataset from the N1freeway (13–6-1). To determine the accuracy of the hybrid model, the observed and predicted output of the traffic volume of long and short trucks at the N1freeway were plotted...
This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc. infrastructurepaperdatasetstraffic-dataspatio-temporaldemand-forecastinggraph-convolutional-networkstraffic-predictiontraffic-flowurban-comput...
Autonomous driving is gradually moving from single-vehicle intelligence to internet of vehicles, where traffic participants can share the traffic flow information perceived by each other. When the sensing technology is combined with the internet of vehic
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 ...
Predict traffic flow with LSTM. For experimental purposes only, unsupported! experimental lstm hyperopt traffic-prediction hyperas Updated Jul 19, 2018 Python aptx1231 / NYC-Dataset Star 51 Code Issues Pull requests Organize some grid-based traffic flow datasets, mainly New York City bicycle and...