Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Archana Venkatachalapathy"'
Autor:
Archana Venkatachalapathy, Mohammed Shaiqur Rahman, Aditya Raj, Jennifer Merickel, Anuj Sharma, Jiyang Wang, Senem Velipasalar
Publikováno v:
International Journal of Automotive Engineering, Vol 14, Iss 3, Pp 66-76 (2023)
Naturalistic driving studies (NDS) are an increasingly popular method to research driving behavior. They often result in large amounts of data varying in source and format (videos, spatial, and time-series data). Traditional data processing systems a
Externí odkaz:
https://doaj.org/article/6e4e73853c67476fa90086ebeb42ab89
Autor:
Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Jiyang Wang, Senem Velipasalar Gursoy, David Anastasiu, Shuo Wang
Publikováno v:
Data in Brief, Vol 46, Iss , Pp 108793- (2023)
This article presents a synthetic distracted driving (SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior and different gaze zones. We collected the data in a stationary vehicle using three in-vehicl
Externí odkaz:
https://doaj.org/article/a19505e87af3494f988b338a72fb8e5b
Publikováno v:
Transportation Research Interdisciplinary Perspectives, Vol 16, Iss , Pp 100703- (2022)
Bicyclists are vulnerable road users who are at a greater risk for injury and fatality during crashes. Additionally, the “near-miss” incidents they experience during regular trips can increase the perceived risk and deter them from riding again.
Externí odkaz:
https://doaj.org/article/0187d8aea7f440f9b1a3291a8fe45265
Autor:
Weiheng Chai, Jiajing Chen, Jiyang Wang, Senem Velipasalar, Archana Venkatachalapathy, Yaw Adu-Gyamfi, Jennifer Merickel, Anuj Sharma
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. :1-10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a890095b5cbdb9e259a6006de550d5e6
https://doi.org/10.1109/tits.2023.3275070
https://doi.org/10.1109/tits.2023.3275070
Autor:
Jiyang Wang, Anuj Sharma, Yaw Adu-Gyamfi, Arya Haghighat, Kai Liang Tan, Senem Velipasalar, Archana Venkatachalapathy, Weiheng Chai
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:10186-10209
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a73451320cc42a5b458709a0a89676f
https://doi.org/10.1109/tits.2021.3126231
https://doi.org/10.1109/tits.2021.3126231
Autor:
Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Alice Li, Shangru Li, Rama Chellappa
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
The 6th edition of the AI City Challenge specifically focuses on problems in two domains where there is tremendous unlocked potential at the intersection of computer vision and artificial intelligence: Intelligent Traffic Systems (ITS), and brick and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e867f8333dc9d55bb1a10145b7b8ef6c
https://doi.org/10.1109/cvprw56347.2022.00378
https://doi.org/10.1109/cvprw56347.2022.00378
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. 2675:317-327
Connected temporary traffic control devices (cTTCDs) that provide their location and status are a new tool that infrastructure owners and operators can begin to use to improve the accuracy of work zone data. By improving work zone data, better inform
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d36d8a8a66553d896e5729373220b01
https://doi.org/10.1177/03611981211011481
https://doi.org/10.1177/03611981211011481
Autor:
Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Jiyang Wang, Senem Velipasalar Gursoy, David Anastasiu, Shuo Wang
Publikováno v:
Data in brief. 46
This article presents a synthetic distracted driving (SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior and different gaze zones. We collected the data in a stationary vehicle using three in-vehicl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a6e60ecbe68d60f83bb8138dd36d1cc
https://pubmed.ncbi.nlm.nih.gov/36506800
https://pubmed.ncbi.nlm.nih.gov/36506800
Publikováno v:
Transportation in Developing Economies. 8
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad4ce16e36472a3c162875b01def4182
https://doi.org/10.1007/s40890-022-00158-3
https://doi.org/10.1007/s40890-022-00158-3
Publikováno v:
Journal of Big Data Analytics in Transportation. 2:181-198
The open data movement has been gaining momentum in the Transportation industry in recent years, with multiple State Departments of Transportation (DOT) launching their own repository of datasets. These actions offer the potential to improve both tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::157216f071723ea53e7f874048fa8d85
https://doi.org/10.1007/s42421-020-00023-y
https://doi.org/10.1007/s42421-020-00023-y