A Survey on Sensor Selection and Placement for Connected and Automated Mobility
The progress towards fully autonomous mobility is significantly impacted by the integration of evolving technologies in connected and automated mobility (CAM). Connected and automated vehicles (CAVs) have the potential to revolutionize our transportation system by improving efficiency, safety, and e...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
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| Online Access: | https://ieeexplore.ieee.org/document/10716737/ |
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| author | Mehmet Kiraz Fikret Sivrikaya Sahin Albayrak |
| author_facet | Mehmet Kiraz Fikret Sivrikaya Sahin Albayrak |
| author_sort | Mehmet Kiraz |
| collection | DOAJ |
| description | The progress towards fully autonomous mobility is significantly impacted by the integration of evolving technologies in connected and automated mobility (CAM). Connected and automated vehicles (CAVs) have the potential to revolutionize our transportation system by improving efficiency, safety, and environmental sustainability. Automated shuttles and public buses, smart traffic signals, intelligent passenger cars, and smart roundabouts are just a few examples of technologies that are being planned and actively researched for integration into transportation systems. Sensors are essential in making this possible. This article provides a structured overview of research on the selection and positioning of sensors on- and off-vehicle to achieve cooperative, connected, and automated mobility. The general integration and usage of sensors in vehicles and infrastructure is described, a detailed taxonomy of the examined research is provided, and future research directions are presented, involving solutions for quantification of sensor performance and addressing current trends. The findings of this article also highlight numerous challenges in creating a universal framework, the lack of application of novel machine learning methods, and the complexity of modeling multi-sensor settings. |
| format | Article |
| id | doaj-art-4dd31177f1de40ee8d96b97a5c549be7 |
| institution | Kabale University |
| issn | 2687-7813 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj-art-4dd31177f1de40ee8d96b97a5c549be72025-01-24T00:02:46ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132024-01-01569271010.1109/OJITS.2024.348132810716737A Survey on Sensor Selection and Placement for Connected and Automated MobilityMehmet Kiraz0https://orcid.org/0000-0002-9380-7908Fikret Sivrikaya1https://orcid.org/0000-0003-0067-4761Sahin Albayrak2https://orcid.org/0000-0001-5092-4584Chair of Agent Technology, Technische Universität Berlin, Berlin, GermanyChair of Agent Technology, Technische Universität Berlin, Berlin, GermanyChair of Agent Technology, Technische Universität Berlin, Berlin, GermanyThe progress towards fully autonomous mobility is significantly impacted by the integration of evolving technologies in connected and automated mobility (CAM). Connected and automated vehicles (CAVs) have the potential to revolutionize our transportation system by improving efficiency, safety, and environmental sustainability. Automated shuttles and public buses, smart traffic signals, intelligent passenger cars, and smart roundabouts are just a few examples of technologies that are being planned and actively researched for integration into transportation systems. Sensors are essential in making this possible. This article provides a structured overview of research on the selection and positioning of sensors on- and off-vehicle to achieve cooperative, connected, and automated mobility. The general integration and usage of sensors in vehicles and infrastructure is described, a detailed taxonomy of the examined research is provided, and future research directions are presented, involving solutions for quantification of sensor performance and addressing current trends. The findings of this article also highlight numerous challenges in creating a universal framework, the lack of application of novel machine learning methods, and the complexity of modeling multi-sensor settings.https://ieeexplore.ieee.org/document/10716737/CAVsCAMITSsensor placementsensor selectionsensor location problem |
| spellingShingle | Mehmet Kiraz Fikret Sivrikaya Sahin Albayrak A Survey on Sensor Selection and Placement for Connected and Automated Mobility IEEE Open Journal of Intelligent Transportation Systems CAVs CAM ITS sensor placement sensor selection sensor location problem |
| title | A Survey on Sensor Selection and Placement for Connected and Automated Mobility |
| title_full | A Survey on Sensor Selection and Placement for Connected and Automated Mobility |
| title_fullStr | A Survey on Sensor Selection and Placement for Connected and Automated Mobility |
| title_full_unstemmed | A Survey on Sensor Selection and Placement for Connected and Automated Mobility |
| title_short | A Survey on Sensor Selection and Placement for Connected and Automated Mobility |
| title_sort | survey on sensor selection and placement for connected and automated mobility |
| topic | CAVs CAM ITS sensor placement sensor selection sensor location problem |
| url | https://ieeexplore.ieee.org/document/10716737/ |
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