Transportation
Making use of a specifically designed SW tool, the authors here presents the results of an activity for the evaluation of energy consumption of buses for urban applications. Both conventional and innovative transport means are considered to obtain interesting comparative conclusions. The SW tool simulates the dynamical behaviour of the vehicles on really measured paths making it possible to evaluate their energetic performances on a Tank to Wheel (TTW) basis. Those data, on such a wide and comparable range were still unavailable in literature.
- Categories:
440 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.
- Categories:
160 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.
- Categories:
466 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.
- Categories:
233 Views
These are tight pedestrian masks for the thermal images present in the KAIST Multispectral pedestrian dataset, available at https://soonminhwang.github.io/rgbt-ped-detection/
Both the thermal images themselves as well as the original annotations are a part of the parent dataset. Using the annotation files provided by the authors, we develop the binary segmentation masks for the pedestrians, using the Segment Anything Model from Meta.
- Categories:
370 Views
Dataset capturedbyrealtimevehicle-mountedcamerasystem, 600 high-quality images was extracted, 480 as training set, 120 as valid set. The images have a resolution of 1600x1200 and encompass three types of pavement defects, that is, cracks, patches and potholes. Our dataset is in YOLO format, YOLO (You Only Look Once) is a popular object detection framework that uses a single neural network to predict bounding boxes and class probabilities for various objects in an image. The YOLO dataset format typically consists of two main components: the image files and the annotation files.
- Categories:
316 Views
Classifying the driving styles is of particular interest for enhancing road safety in smart cities. The vehicle can assist the driver by providing advice to increase awareness of potential dangers. Accordingly, dissuasive measures, such as adjusting insurance costs, can be implemented. The service is called Pay-As-You-Drive insurance (PAYD), and to address it, the paper introduces a method for constructing a database of simulated driver behaviors using the Simulation of Urban MObility Simulation of Urban MObility (SUMO) simulator.
- Categories:
231 Views
The JKU-ITS AVDM contains data from 17 participants performing different tasks with various levels of distraction.
The data collection was carried out in accordance with the relevant guidelines and regulations and informed consent was obtained from all participants.
The dataset was collected using the JKU-ITS research vehicle with automated capabilities under different illumination and weather conditions along a secure test route within the
- Categories:
648 Views
The Partial Discharge - Localisation Dataset, abbreviated: PD-Loc Dataset is an extensive collection of acoustic data specifically curated for the advancement of Partial Discharge (PD) localisation techniques within electrical machinery. Developed using a precision-engineered 32-sensor acoustic array, this dataset encompasses a wide array of signals, including chirps, white Gaussian noise, and PD signals.
- Categories:
727 Views
The datasets comprise configurations of loading and unloading plans for container ships, generated under six distinct scenarios based on varying numbers of stacks and maximum stack heights of containers in each row. Considering typical container ship characteristics, scenarios encompass stack numbers ranging from 5 to 30 and maximum stack heights from 4 to 10. The dataset includes loading and unloading plans for dockyard containers, with sample plans provided for small ships. Each of the 5 datasets comprises 20 instances representing different container loading and unloading scenarios.
- Categories:
169 Views