Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107477
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Computing | - |
dc.creator | Nawaz, M | - |
dc.creator | Tang, JKT | - |
dc.creator | Bibi, K | - |
dc.creator | Xiao, S | - |
dc.creator | Ho, HP | - |
dc.creator | Yuan, W | - |
dc.date.accessioned | 2024-06-25T04:31:16Z | - |
dc.date.available | 2024-06-25T04:31:16Z | - |
dc.identifier.issn | 1524-9050 | - |
dc.identifier.uri | http://hdl.handle.net/10397/107477 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication M. Nawaz, J. K. -T. Tang, K. Bibi, S. Xiao, H. -P. Ho and W. Yuan, "Robust Cognitive Capability in Autonomous Driving Using Sensor Fusion Techniques: A Survey," in IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 5, pp. 3228-3243, May 2024 is available at https://doi.org/10.1109/TITS.2023.3327949. | en_US |
dc.subject | Autonomous vehicles | en_US |
dc.subject | LiDAR points | en_US |
dc.subject | Object detection | en_US |
dc.subject | Object tracking | en_US |
dc.subject | Radar points | en_US |
dc.subject | RGB cameras | en_US |
dc.subject | Sensor fusion | en_US |
dc.title | Robust cognitive capability in autonomous driving using sensor fusion techniques : a survey | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 3228 | - |
dc.identifier.epage | 3243 | - |
dc.identifier.volume | 25 | - |
dc.identifier.issue | 5 | - |
dc.identifier.doi | 10.1109/TITS.2023.3327949 | - |
dcterms.abstract | Autonomous driving has become a prominent topic with the rise of intelligent urban vision in communities. Advancements in automated driving technology play a significant role in the intelligent transportation system. Autonomous vehicles (AVs) rely heavily on sensor technologies as they are responsible for navigating safely through their environment and avoiding obstacles. This paper aims to outline the vital role of sensor fusion in intelligent transportation systems. Sensor fusion is the process of combining data from multiple sensors to obtain more comprehensive measurements and greater cognitive abilities than a single sensor could achieve. By merging data from different sensors, it ensures that driving decisions are based on reliable data, with improved accuracy, reliability, and robustness in AVs. This paper provides a comprehensive review of AV capacity, impacts, planning, technological challenges, and omitted concerns. We used state-of-the-art evaluation tools to check the performance of different sensor fusion algorithms in AVs. This paper will help us to determine our position, direction, the impacts of AVs on society, the need for smart city mobility outcomes, and the way to solve the auto industry challenges in the future. The analysis of AV systems from the perspective of sensor fusion in this research is expected to be beneficial to current and future researchers. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE transactions on intelligent transportation systems, May 2024, v. 25, no. 5, p. 3228-3243 | - |
dcterms.isPartOf | IEEE transactions on intelligent transportation systems | - |
dcterms.issued | 2024-05 | - |
dc.identifier.scopus | 2-s2.0-85177046820 | - |
dc.identifier.eissn | 1558-0016 | - |
dc.description.validate | 202406 bcch | - |
dc.description.oa | Author’s Original | en_US |
dc.identifier.FolderNumber | a2886 | en_US |
dc.identifier.SubFormID | 48648 | en_US |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | Green (AO) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Nawaz_Robust_Cognitive_Capability.pdf | Preprint version | 4.25 MB | Adobe PDF | View/Open |
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