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- Creator:
- Klinich, Kathleen D, Lin, Brian, and Moore, Jamie L.
- Description:
- This dataset allows comparison of the different strategies implemented by vehicle manufacturers being used to communicate with drivers. Spreadsheets were created in MS Excel to summarize data for each vehicle, and include page numbers in each vehicle owner's manual for reference. The photos taken of each vehicle control panel allow detailed inspection of the displays and controls.
- Keyword:
- vehicle, controls, displays, and FMVSS 101
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal imaging, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Yining Shi
- Description:
- Statistical study of residuals between Swarm observations and IGRF-13 geomagnetic field model larger than 300 nT in northern and southern hemisphere. Data analysis done on https://viresclient.readthedocs.io/en/latest/ These data are generated to conduct a statistical study of the locations of large residuals in the two hemispheres for a better understanding of potential error in satellite aviation application when using Earth magnetic field models like IGRF as references, as well as the energy transfer in the magnetosphere-ionosphere-thermosphere coupling. Interhemispheric asymmetries are found in the locations of the large residuals due to the difference in geographic pole locations.
- Discipline:
- Engineering
-
- Creator:
- Rivera-Rivera, Luis Y., Moore, Timothy C., and Glotzer, Sharon C.
- Description:
- The dataset is organized as follows: the data for each of the three target structures is contained within a directory with the structure name (e.g., kagome, pyrocholore and snub-square). Within each structure directory, data obtained from alchemical and self-assembly simulations are separated into alchem and self-assembly directories respectively. An additional suboptimal-self-assembly directory is only present for the snub-square structure and contains the data for the pattern registration analysis discussed in the SI. For a detailed description of each file contained within each directory, please refer to the README file.
- Keyword:
- inverse design, self-assembly, triblock Janus particles, crystallization slot, and digital alchemy
- Citation to related publication:
- Rivera-Rivera, LY, Moore, TC & SC Glotzer. Inverse design of triblock Janus spheres for self-assembly of complex structures in the crystallization slot via digital alchemy. Soft Matter, 2023, 19, 2726-2736 doi: 10.1039/d2sm01593e
- Discipline:
- Engineering