Transportation

This dataset comprises ten adapted benchmark instances derived from the classical Prodhon dataset, along with one dataset based on a real-world logistics case study. The data are specifically designed to support the evaluation of a bi-objective Green Location Routing Problem (GLRP) model that aims to optimize both economic cost and environmental impact (carbon emissions).

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The data is derived from 22,898 comments on driverless and human driving obtained by crawler technology on China's Weibo and XiaoHongshu platforms from May 1 to August 31, 2024. The main data formats are xlsx, py, txt, json and so on. The files in py format are script files, which are used to process data. The dataset was eventually used for topic mining, sentiment analysis, and more on Chinese users' comments on driverless and human driving.

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The dataset contains 56 rows and 51 columns, detailing various characteristics of EV charging stations (SPKLU) in the Jadetabek area. Key attributes include station identifiers, transaction metrics (e.g., number of transactions, unique users, average duration), geospatial data (latitude, longitude, easting, northing), administrative divisions, and location criteria. It also captures proximity to infrastructure such as roads, toll gates, and other EV stations, alongside charger counts for different types, population metrics, and income levels.

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216 Views

The U.S. delay dataset is collected from Kaggle(https://www.kaggle.com/datasets/robikscube/flight-delay-dataset-20182022), covering three years of flight data from January 1, 2017, to December 31, 2019. The dataset originally collected includes data from 360 airports. We remove airports with fewer annual flight numbers and select data from 75 medium and large airports for our experiments.

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84 Views

Repeated Route Naturalistic Driving Dataset (R2ND2) is a dual-perspective dataset for driver behavior analysis constituent of vehicular data collected using task-specific CAN decoding sensors using OBD port and external sensors, and (b) gaze-measurements collected using industry-standard multi-camera gaze calibration and collection system. Our experiment is designed to consider the variability associated with driving experience that depends on the time of day and provides valuable insights into the correlation of these additional metrics on driver behavior.

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448 Views

The AIS dataset is provided by the National Oceanic and Atmospheric Administration (NOAA), spanning from January 2020 to December 2020. The trajectories of 140 individual vessels (including tankers and cargo) were collected. Weather and ocean conditions for the same period are obtained from the National Data Buoy Center (NDBC), collected from 15 buoys. 

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81 Views

This is a dataset related to spatial crowdsourcing, encompassing data on workers and tasks. The urban spatial data is sourced from an open dataset, and its website link has been provided in the paper.

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42 Views

The datasets are sourced from the Caltrans Performance Measurement System (PeMS) in California, which monitors and collects real-time traffic data from over 39,000 sensors deployed on major highways throughout the state. The PeMS system collects data every 30 seconds and aggregates it into 5-minute interval, with each sensor generating data for 288 time steps daily. Additionally, road network structure data is derived from the connectivity status and actual distances between sensors.

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595 Views

Ground Penetrating Radar (GPR) facilitates the detection and localisation of subsurface structural anomalies in critical transport infrastructure (e.g. tunnels), better informing targeted maintenance strategies. However, conventional fixed-directional systems suffer from limited coverage - especially of less-accessible structural aspects (e.g. crowns) - alongside unclear visual output of anomaly spatial profiles, both for physical and simulated datasets.

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535 Views

We present a comprehensive multi-sensor dataset comprising 4D mmWave radar point clouds, lidar point clouds, and camera images in the open-pit mine. The dataset encompasses various operational scenarios, including the dumping site, loading site, connecting roads, and haulage maintenance area, under various lighting conditions such as cloudy, dark, daylight, and overcast skies.

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389 Views

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