5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2023 |
| Tipo de documento: | Dissertação |
| Idioma: | eng |
| Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Texto Completo: | http://hdl.handle.net/10400.22/23704 |
Resumo: | Humanity is progressively moving towards a more intuitive and technological future. The area of Intelligent and Cooperative Transport Systems has revealed itself as one of the areas in great evolution, through technologies of autonomous driving and intravehicle communication. With the main goal of providing accident-free environments as well as optimizing the movement of vehicles on roads all over the world, Vehicle to Everything (V2X) communication is very important when it comes to all kinds of vehicular applications. The CMU|PT FLOYD project focuses on this area, with the aim of developing new systems for possible future implementation. In this report, a vehicular application using a 5G-capable module to perform Vehicle to Infrastructure (V2I) communications was evaluated. This vehicular application is based on an emergency braking scenario, whereby detecting an approaching vehicle in a place where an accident occurred, a message is sent over the network that is picked up by the main vehicle, triggering braking. It should be noted that this sending will be made through the module with 5G capacity, thus being an innovative application. Complementary to this scenario is the tracking of a vehicle by another vehicle, thus making a more complex emergency braking application with a cooperative platoon. This platoon will be maintained through sensors present in the following vehicle, such as LiDAR and ZED camera. With this, image processing and a sensor fusion was done in order to keep the follower at a safe distance but with the ability to follow the leader. In order to validate and test this entire solution, robotic testbeds were used as a low-cost solution, allowing a concrete evaluation, with enlightening physical results of the entire application performed. |
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5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed5GV2XRobotic TestbedModuleVehiclePlatoonImage ProcessingSensor FusionPelotãoVeículosFusão de SensoresMóduloHumanity is progressively moving towards a more intuitive and technological future. The area of Intelligent and Cooperative Transport Systems has revealed itself as one of the areas in great evolution, through technologies of autonomous driving and intravehicle communication. With the main goal of providing accident-free environments as well as optimizing the movement of vehicles on roads all over the world, Vehicle to Everything (V2X) communication is very important when it comes to all kinds of vehicular applications. The CMU|PT FLOYD project focuses on this area, with the aim of developing new systems for possible future implementation. In this report, a vehicular application using a 5G-capable module to perform Vehicle to Infrastructure (V2I) communications was evaluated. This vehicular application is based on an emergency braking scenario, whereby detecting an approaching vehicle in a place where an accident occurred, a message is sent over the network that is picked up by the main vehicle, triggering braking. It should be noted that this sending will be made through the module with 5G capacity, thus being an innovative application. Complementary to this scenario is the tracking of a vehicle by another vehicle, thus making a more complex emergency braking application with a cooperative platoon. This platoon will be maintained through sensors present in the following vehicle, such as LiDAR and ZED camera. With this, image processing and a sensor fusion was done in order to keep the follower at a safe distance but with the ability to follow the leader. In order to validate and test this entire solution, robotic testbeds were used as a low-cost solution, allowing a concrete evaluation, with enlightening physical results of the entire application performed.Santos, Pedro Miguel Salgueiro dosREPOSITÓRIO P.PORTOPereira, João Filipe Mateus2023-10-18T11:09:49Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.22/23704urn:tid:203367510enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-07T10:21:41Zoai:recipp.ipp.pt:10400.22/23704Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:50:12.736502Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed |
| title |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed |
| spellingShingle |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed Pereira, João Filipe Mateus 5G V2X Robotic Testbed Module Vehicle Platoon Image Processing Sensor Fusion Pelotão Veículos Fusão de Sensores Módulo |
| title_short |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed |
| title_full |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed |
| title_fullStr |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed |
| title_full_unstemmed |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed |
| title_sort |
5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed |
| author |
Pereira, João Filipe Mateus |
| author_facet |
Pereira, João Filipe Mateus |
| author_role |
author |
| dc.contributor.none.fl_str_mv |
Santos, Pedro Miguel Salgueiro dos REPOSITÓRIO P.PORTO |
| dc.contributor.author.fl_str_mv |
Pereira, João Filipe Mateus |
| dc.subject.por.fl_str_mv |
5G V2X Robotic Testbed Module Vehicle Platoon Image Processing Sensor Fusion Pelotão Veículos Fusão de Sensores Módulo |
| topic |
5G V2X Robotic Testbed Module Vehicle Platoon Image Processing Sensor Fusion Pelotão Veículos Fusão de Sensores Módulo |
| description |
Humanity is progressively moving towards a more intuitive and technological future. The area of Intelligent and Cooperative Transport Systems has revealed itself as one of the areas in great evolution, through technologies of autonomous driving and intravehicle communication. With the main goal of providing accident-free environments as well as optimizing the movement of vehicles on roads all over the world, Vehicle to Everything (V2X) communication is very important when it comes to all kinds of vehicular applications. The CMU|PT FLOYD project focuses on this area, with the aim of developing new systems for possible future implementation. In this report, a vehicular application using a 5G-capable module to perform Vehicle to Infrastructure (V2I) communications was evaluated. This vehicular application is based on an emergency braking scenario, whereby detecting an approaching vehicle in a place where an accident occurred, a message is sent over the network that is picked up by the main vehicle, triggering braking. It should be noted that this sending will be made through the module with 5G capacity, thus being an innovative application. Complementary to this scenario is the tracking of a vehicle by another vehicle, thus making a more complex emergency braking application with a cooperative platoon. This platoon will be maintained through sensors present in the following vehicle, such as LiDAR and ZED camera. With this, image processing and a sensor fusion was done in order to keep the follower at a safe distance but with the ability to follow the leader. In order to validate and test this entire solution, robotic testbeds were used as a low-cost solution, allowing a concrete evaluation, with enlightening physical results of the entire application performed. |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023-10-18T11:09:49Z 2023 2023-01-01T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
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http://hdl.handle.net/10400.22/23704 urn:tid:203367510 |
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urn:tid:203367510 |
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eng |
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eng |
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openAccess |
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application/pdf |
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