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Vehicle Trajectory Datasets for ITS, smart city, and mobile crowdsensing

We appreciate your interests in the datasets, which contain various categories of data. Please see details below.

1) Thanks for your attention on the private car trajectory dataset collected through our algorithms and devices.

Remarks:The process of trajectory collection and data transmission is purely anonymous. Specifically, it is not to collect any personal information regarding the vehicles (the vehicle ID has been anonymized as a bit string) as well as the drivers. For the collection of the trajectory dataset, we ensure that the users have well understood the process of the data collection. In other words, the usage of data collection devices is entirely up to the users and they are fully aware of the processing of trajectory collection. We have received the approval from the users before we install devices on their vehicles. In addition, they gave their consent to educational institutions to study and use their data for research purposes.

Now, we offer free and public access to our dataset, please feel free to use our data on nonprofit, scientific purposes. If you would like to access the data, please sign the agreement and send a scanned copy to us via zhxiao@hnu.edu.cn. In 14 working days, we will send you our dataset as well as the Python code packet. The ‘ReadMe.doc’ in the packet gives a detailed instruction of the Python code to run the algorithm based on our private car trajectory dataset.

Indeed, our trajecotory dataset has received wide interests both from the industry and academic. At present, in response to the requests on the data, we have shared the vehicle trajectory dataset to more than 20 institutes around the world. We are happy to see that our vehicle trajectory data can promote the researches and applications in driving behavior analysis, collision avoidance systems, intelligent transportation systems, usage based insurance (UBI), urban planning etc.

Please find the agreement below: https://github.com/HunanUniversityZhuXiao/PrivateCarTrajectoryData/blob/master/Trajectory-data-license-v3.pdf

If you are unable to download the agreement, please send the request to us via zhxiao@hnu.edu.cn. For details of our research, please refer to https://zhuxiao-hnu.github.io/en/

2) At present, Zhejiang Lab has established a cooperative relationship with Hunan University, shared and uploading various datasets, including the private car trajectory data, bicycle trajectory data and data on disease transmission. We welcome to apply, together engaged in data mining and data analysis related academic research.

Please contact Dr. Hongyang Chen via hongyang@zhejianglab.com

For details, please refer to https://jp.linkedin.com/in/hongyangchen

3) Here is our Instagram dataset regarding the Coronavirus content published during the first wave of the pandemic in 2020 (https://arxiv.org/abs/2004.12226). This is the download link (raw data) available in Google Drive. https://drive.google.com/file/d/1sXebQD-5eFWQlg4Vst8baWzj4g-orCEc/view?usp=drivesdk Instruction: There are three python pkl files (post/comment/like) and a Jupyter Notebook Document to read the dataset as Pandas Dataframe. Images are stored in binary format. The second release is coming soon.

Please contact Prof. Noël Crespi for details.

Noël Crespi, Professor Head of Data Intelligence and Communication Engineering Laboratory Telecom SudParis, Institut Polytechnique de Paris 9 rue C. Fourier, 91011 Evry, France, +33 160 76 46 23 https://dice.wp.telecom-sudparis.eu/

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