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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Driving environmental images from on-board camera and RTK-based localization for autonomous vehicles

Authors: Artuñedo, Antonio; Godoy, Jorge; Villagra, Jorge;

Driving environmental images from on-board camera and RTK-based localization for autonomous vehicles

Abstract

This dataset contains images from an on-board frontal camera as well as information of the vehicle state, including: accurate global localization, heading, speed, acceleration and steering angle position. The data was captured from one of the vehicle instrumenhted vehicles of the AUTOPIA group at the surrounding of the Centre for Automation and Robotics, in Arganda del Rey (Madrid, Spain). The dataset is aimed to help users in developing and improving image-based road detection algorithms, as well as machine learning end-to-end approaches using driving information provided (steering angle, vehicle speed, etc.). The dataset has also been used to develop algorithms for online map adaptation based on computer vision. Please, refer to: "Artuñedo, A. (2020). Decision-making Strategies for Automated Driving in Urban Environments. In Springer Theses. Springer International Publishing. https://doi.org/10.1007/978-3-030-45905-5" Image information The sequence of images is provided in PNG format, and is named following the pattern: 'l_sA_nsB.png', where A and B are the second and nanosecond when the image was captured, so that A+B*1e-9 is the capture time. The images were captuted with the camera Bumblebee 2 0,8 MP Color FireWire 1394a 3,8mm (Sony ICX204) with the following technical features: Sensor type: CCD Sensor format: 1/3" Pixel size 4.65 µm Focal length: 3.8mm Fames per second: 20 fps Resolution: 1024 x 768 Camera position The camera is placed at a height 1290 mm measured from the ground plane. With respect to the vehicle frame, it has a yaw of -2º and a pitch 5.5º, in order to focus the field of view in the road. Vehicle localization The test vehicle is a prototype of Autonomous Vehicle developed by the AUTOPIA reseach group at the Centre for Automation and Robotics in Spain. Vehicle location mainly depends on a Trimble BX982 GNSS receiver using RTK. The GNSS antenna is installed near the rear axle of the vehicle, in the middle part of the vehicle. However, the location algorithm applies an EKF for combining GNSS measurements with different onboard sensors providing yaw rate, longitudinal acceleration and speed, steering wheel position and speed, etc. The vehicle localization file ('vehicle_data.csv') includes the following data at a sample rate of 20 Hz: Time (s) UTM East (m) UTM North (m) Orientation (º) Speed (m/s) Acceleration(m/s^2) Steering wheel angle (º) Disclaimer That the dataset comes "AS IS", without express or implied warranty and/or any liability exceeding mandatory statutory obligations. This especially applies to any obligations of care or indemnification in connection with the dataset. The dataset was created for our research purposes only and no quality assessment was done for the usage in products of any kind. We can therefore not guarantee for the correctness, completeness or reliability of the provided data set.

Keywords

Vehicle localization, GNSS, RTK, Machine learning, Connected and Autonomous Vehicles, Camera, ITS

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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