Vehicular localization using 5G V2X
With rapid advancements in automotive fields, self-driving cars are gradually transferred from labs to roads in our real lives. One key factor for fully automatic driving is the absolute and relative positioning between vehicles, road-side units and pedestrians. Besides, the accurate and real-tim...
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sg-ntu-dr.10356-1575492023-07-07T19:17:06Z Vehicular localization using 5G V2X Pan, Yongqi Tay Wee Peng School of Electrical and Electronic Engineering wptay@ntu.edu.sg Engineering::Electrical and electronic engineering With rapid advancements in automotive fields, self-driving cars are gradually transferred from labs to roads in our real lives. One key factor for fully automatic driving is the absolute and relative positioning between vehicles, road-side units and pedestrians. Besides, the accurate and real-time localization of vehicles is a necessary requirement for various vehicle-related services like accident prevention and routing services. Using cellular radio signals transmitted by the devices mounted on the car is a possible method to estimate the position of the vehicle. It has aroused more interest due to its high accuracy in localization which can be used for more services. More recently, the emergence of 5G New Radio (NR) is believed to bring a wider range of localization use cases since the Cellular V2X is standardized by the third-generation partnership project (3GPP). The mmWave signals which belong to 5G NR and have a higher frequency are considered as the future trend in signal communication. This project will discuss on different vehicle positioning methods related to the 5G V2X. Besides, a simulation solution using mmWave signals to complete vehicle positioning will be given. Last, there will be investigations on relevant parameters to see their impact on the positioning accuracy. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-19T12:59:38Z 2022-05-19T12:59:38Z 2022 Final Year Project (FYP) Pan, Y. (2022). Vehicular localization using 5G V2X. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157549 https://hdl.handle.net/10356/157549 en A3250-211 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Pan, Yongqi Vehicular localization using 5G V2X |
description |
With rapid advancements in automotive fields, self-driving cars are gradually transferred
from labs to roads in our real lives. One key factor for fully automatic driving is the
absolute and relative positioning between vehicles, road-side units and pedestrians.
Besides, the accurate and real-time localization of vehicles is a necessary requirement for
various vehicle-related services like accident prevention and routing services.
Using cellular radio signals transmitted by the devices mounted on the car is a possible
method to estimate the position of the vehicle. It has aroused more interest due to its high
accuracy in localization which can be used for more services. More recently, the
emergence of 5G New Radio (NR) is believed to bring a wider range of localization use
cases since the Cellular V2X is standardized by the third-generation partnership project
(3GPP). The mmWave signals which belong to 5G NR and have a higher frequency are
considered as the future trend in signal communication.
This project will discuss on different vehicle positioning methods related to the 5G V2X.
Besides, a simulation solution using mmWave signals to complete vehicle positioning will
be given. Last, there will be investigations on relevant parameters to see their impact on
the positioning accuracy. |
author2 |
Tay Wee Peng |
author_facet |
Tay Wee Peng Pan, Yongqi |
format |
Final Year Project |
author |
Pan, Yongqi |
author_sort |
Pan, Yongqi |
title |
Vehicular localization using 5G V2X |
title_short |
Vehicular localization using 5G V2X |
title_full |
Vehicular localization using 5G V2X |
title_fullStr |
Vehicular localization using 5G V2X |
title_full_unstemmed |
Vehicular localization using 5G V2X |
title_sort |
vehicular localization using 5g v2x |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/157549 |
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1772828887684743168 |