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- Publisher Website: 10.1109/ACCESS.2021.3074996
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Article: IEEE Access Special Section Editorial: Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems
Title | IEEE Access Special Section Editorial: Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems |
---|---|
Authors | |
Issue Date | 2021 |
Publisher | Institute of Electrical and Electronics Engineers: Open Access Journals. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639 |
Citation | IEEE Access, 2021, v. 9, p. 69492-69497 How to Cite? |
Abstract | The topic of Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems (ITS) has drawn more attention recently, with the rapid development of ubiquitous networks and smart vehicles. Researchers around the world have been working on new automotive applications to create a comfortable and safer driving environment. Current challenges include: how to run computing-intensive applications on vehicles; how to enable real-time feedback between vehicles and the traffic management server based on the current Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication modes; and how to provide efficient computing capabilities for resource-consumption applications and reasonable resource allocation for vehicles and infrastructures. Recently, AI has made remarkable achievements in many fields such as image processing, pattern recognition, and natural language processing. It is also involved in computing-intensive applications, such as autopilot and real-time navigation through V2V or V2I. However, AI-Empowered ITS is still in its infancy. How can AI be integrated with ITS and function well in dynamic vehicular network scenarios? In addition, there are still questions on how to design more efficient AI solutions for resource management and coordination in ITS. |
Persistent Identifier | http://hdl.handle.net/10722/304675 |
ISSN | 2023 Impact Factor: 3.4 2023 SCImago Journal Rankings: 0.960 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Ngai, E | - |
dc.contributor.author | Chen, C | - |
dc.contributor.author | Tolba, AM | - |
dc.contributor.author | Obaidat, MS | - |
dc.contributor.author | Wang, F | - |
dc.date.accessioned | 2021-10-05T02:33:32Z | - |
dc.date.available | 2021-10-05T02:33:32Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | IEEE Access, 2021, v. 9, p. 69492-69497 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | http://hdl.handle.net/10722/304675 | - |
dc.description.abstract | The topic of Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems (ITS) has drawn more attention recently, with the rapid development of ubiquitous networks and smart vehicles. Researchers around the world have been working on new automotive applications to create a comfortable and safer driving environment. Current challenges include: how to run computing-intensive applications on vehicles; how to enable real-time feedback between vehicles and the traffic management server based on the current Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication modes; and how to provide efficient computing capabilities for resource-consumption applications and reasonable resource allocation for vehicles and infrastructures. Recently, AI has made remarkable achievements in many fields such as image processing, pattern recognition, and natural language processing. It is also involved in computing-intensive applications, such as autopilot and real-time navigation through V2V or V2I. However, AI-Empowered ITS is still in its infancy. How can AI be integrated with ITS and function well in dynamic vehicular network scenarios? In addition, there are still questions on how to design more efficient AI solutions for resource management and coordination in ITS. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers: Open Access Journals. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639 | - |
dc.relation.ispartof | IEEE Access | - |
dc.rights | IEEE Access. Copyright © Institute of Electrical and Electronics Engineers: Open Access Journals. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | IEEE Access Special Section Editorial: Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems | - |
dc.type | Article | - |
dc.identifier.email | Ngai, E: chngai@eee.hku.hk | - |
dc.identifier.authority | Ngai, E=rp02656 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/ACCESS.2021.3074996 | - |
dc.identifier.scopus | eid_2-s2.0-85106035417 | - |
dc.identifier.hkuros | 325888 | - |
dc.identifier.volume | 9 | - |
dc.identifier.spage | 69492 | - |
dc.identifier.epage | 69497 | - |
dc.identifier.isi | WOS:000650445400001 | - |
dc.publisher.place | United States | - |