Zobrazeno 1 - 10
of 3 592
pro vyhledávání: '"connected vehicles"'
Publikováno v:
Transport and Telecommunication, Vol 25, Iss 3, Pp 278-288 (2024)
This paper addresses the vulnerability of vehicular ad hoc networks (VANETs) to malicious attacks, specifically focusing on position falsification attacks. Detecting misbehaving vehicles in VANETs is challenging due to the dynamic nature of the netwo
Externí odkaz:
https://doaj.org/article/84f3fac4cea94b7d92d0f7d45380821d
Autor:
Amanda R. Siems‐Anderson
Publikováno v:
Meteorological Applications, Vol 31, Iss 4, Pp n/a-n/a (2024)
Abstract Vehicle‐based mobile observations are taken across the world every day by operational and research meteorological organizations, public transportation agencies, and private car manufacturers. Whether directly weather‐related (e.g., air t
Externí odkaz:
https://doaj.org/article/7ea9db32336b4bd696a0be175e84b2ec
Publikováno v:
Elektronika ir Elektrotechnika, Vol 30, Iss 1, Pp 56-67 (2024)
Connected vehicle (CV) technology has revolutionised the intelligent transportation management system by providing new perspectives and opportunities. To further improve risk perception and early warning capabilities in intricate traffic scenarios, a
Externí odkaz:
https://doaj.org/article/8be67c21f744483ebe3e61e90793183d
Autor:
Praveen Abbaraju, Subrata Kumar Kundu
Publikováno v:
IEEE Open Journal of Intelligent Transportation Systems, Vol 5, Pp 445-453 (2024)
Electric vehicles (EV) are gaining wide traction and popularity despite the operational range and charging time limitations. Therefore, to ensure the reliability of EVs for realizing improved customer satisfaction, it is necessary to monitor and trac
Externí odkaz:
https://doaj.org/article/ebb7a354e81d4457b12058cd2edd4f01
Publikováno v:
International Journal of Cognitive Computing in Engineering, Vol 5, Iss , Pp 297-306 (2024)
Data about vehicle trajectories assumes a crucial role in applications such as intelligent connected vehicles. However, missing values resulting from sensors and other factors frequently affect real trajectory data. Currently, it is challenging to ut
Externí odkaz:
https://doaj.org/article/5161ef831cba4829a7802e0e897857fa
Autor:
Baekgyu Kim, Deepak Gangadharan
Publikováno v:
IEEE Access, Vol 12, Pp 89082-89097 (2024)
Edge server-assisted computation offloading enables vehicles to leverage server compute resources to deliver connected services, overcoming the limitations of onboard resources. Understanding the compute workloads of edge servers is crucial for effec
Externí odkaz:
https://doaj.org/article/3f3d9ee0b74a42358ffed4ac168f43d1
Publikováno v:
IEEE Access, Vol 12, Pp 43721-43733 (2024)
Automated and connected vehicles are emerging in the market. Currently, solutions are being proposed to use these technologies for cooperative driving, which can significantly improve road safety. Vehicular safety applications must be tested before d
Externí odkaz:
https://doaj.org/article/a0378a22658542919736e215bafa97f3
Publikováno v:
IEEE Access, Vol 12, Pp 19250-19276 (2024)
In Intelligent Transportation Systems (ITS), ensuring road safety has paved the way for innovative advancements such as autonomous driving. These self-driving vehicles, with their variety of sensors, harness the potential to minimize human driving er
Externí odkaz:
https://doaj.org/article/2874447c68bb499a9919cb06e9854191
Autor:
Ashkan Gholamhosseinian, Jochen Seitz
Publikováno v:
IEEE Open Journal of Vehicular Technology, Vol 5, Pp 230-243 (2024)
This paper introduces a novel centralized autonomous inclusive intersection management mechanism (CAI2M2) for heterogeneous connected vehicles (HCVs). The system embraces a diverse array of human-driven vehicles, each possessing unique characteristic
Externí odkaz:
https://doaj.org/article/3b2e2a4d0bd04970b3dfa12924f8a0a6
Autor:
Mehr, Goodarz
Doctor of Philosophy
Self-driving cars promise a future with safer roads and reduced traffic incidents and fatalities. This future hinges on the car's accurate understanding of its surrounding environment; however, the reliability of the algorit
Self-driving cars promise a future with safer roads and reduced traffic incidents and fatalities. This future hinges on the car's accurate understanding of its surrounding environment; however, the reliability of the algorit
Externí odkaz:
https://hdl.handle.net/10919/119208