Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Hesham Alghodhaifi"'
Autor:
Hesham Alghodhaifi, Sridhar Lakshmanan
Publikováno v:
Sensors, Vol 23, Iss 17, p 7361 (2023)
Ensuring that intelligent vehicles do not cause fatal collisions remains a persistent challenge due to pedestrians’ unpredictable movements and behavior. The potential for risky situations or collisions arising from even minor misunderstandings in
Externí odkaz:
https://doaj.org/article/85d5c61a2b484a008adf32d2ad56151d
Autor:
Hesham Alghodhaifi, Sridhar Lakshmanan
Publikováno v:
IEEE Access, Vol 9, Pp 151531-151566 (2021)
In recent years, autonomous vehicles (AVs), which observe the driving environment and lead a few or all of the driving tasks, have garnered tremendous success. The field of AVs has been rapidly developing and has found many applications. As a safety
Externí odkaz:
https://doaj.org/article/2c7260ac1c3a4f0b89aa4128eac6ddc2
Autor:
Hesham Alghodhaifi, Sridhar Lakshmanan
Publikováno v:
Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2020.
Conflict analysis using surrogate safety measures (SSMs) has turned into an efficient way to investigate safety issues in autonomous vehicles. Previous studies largely focus on video images taken from high elevation. However, it involves overwhelming
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d767ca666d4a6f4b09dc8a93e3255fb
https://doi.org/10.1117/12.2558830
https://doi.org/10.1117/12.2558830
Publikováno v:
Unmanned Systems Technology XXII.
In this paper, we have analyzed scenarios for leader-follower vehicle convoys that have the potential to be unsafe, hazardous, or even fatal in order to provide insight on dangerous driving conditions for autonomous vehicle platoons. These scenarios
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ea3530be0f90d44abd5610e91d303bf
https://doi.org/10.1117/12.2558925
https://doi.org/10.1117/12.2558925
Publikováno v:
2019 IEEE National Aerospace and Electronics Conference (NAECON).
Over the past ten years, there has been a rise in using deep learning for medical image analysis such as CNN. Deep learning is used extensively in the field of healthcare to identify patterns, classify and segment tumors and so on. The classification
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4151f2bde7a61ef2d33be0aecd528efe
https://doi.org/10.1109/naecon46414.2019.9057822
https://doi.org/10.1109/naecon46414.2019.9057822
Publikováno v:
Unmanned Systems Technology XXI.
In this paper, we present results obtained through simulation of connected-autonomous semi-trucks that are operating in a leader-follower configuration. Autonomy is enabled in this configuration with a very lean sensor package on each truck, precisio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c91e15df963679b0aaeb3c4df3a7b28d
https://doi.org/10.1117/12.2520485
https://doi.org/10.1117/12.2520485
Publikováno v:
2017 IEEE Conference on Energy Conversion (CENCON).
This paper deals with the design and modeling aspects of the Ni-MH (Nickle metal hydride) battery and measures the SOC (State of charge) using different methods. This research deals with mathematical modeling, analysis of stability, analysis of step
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c125d60b7a5e8289057982a66baa0e7
https://doi.org/10.1109/cencon.2017.8262459
https://doi.org/10.1109/cencon.2017.8262459