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Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State

The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space r...

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Detalles Bibliográficos
Autores principales: Piao, Changhao, Zhang, Jun, Chang, KyungHi, Li, Yan, Liu, Mingjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037424/
https://www.ncbi.nlm.nih.gov/pubmed/33804891
http://dx.doi.org/10.3390/s21072261
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author Piao, Changhao
Zhang, Jun
Chang, KyungHi
Li, Yan
Liu, Mingjie
author_facet Piao, Changhao
Zhang, Jun
Chang, KyungHi
Li, Yan
Liu, Mingjie
author_sort Piao, Changhao
collection PubMed
description The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space recognition error and trajectory generation for vehicle nonparallel initial state with parking space. In this study, the authors propose multi-sensor information ensemble for parking space recognition and adaptive trajectory generation method, which is also robust to vehicle nonparallel initial state. Both simulation and real vehicle experiments are conducted to prove that the proposed method can improve the automatic parking system performance.
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spelling pubmed-80374242021-04-12 Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State Piao, Changhao Zhang, Jun Chang, KyungHi Li, Yan Liu, Mingjie Sensors (Basel) Article The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space recognition error and trajectory generation for vehicle nonparallel initial state with parking space. In this study, the authors propose multi-sensor information ensemble for parking space recognition and adaptive trajectory generation method, which is also robust to vehicle nonparallel initial state. Both simulation and real vehicle experiments are conducted to prove that the proposed method can improve the automatic parking system performance. MDPI 2021-03-24 /pmc/articles/PMC8037424/ /pubmed/33804891 http://dx.doi.org/10.3390/s21072261 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Piao, Changhao
Zhang, Jun
Chang, KyungHi
Li, Yan
Liu, Mingjie
Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State
title Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State
title_full Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State
title_fullStr Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State
title_full_unstemmed Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State
title_short Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State
title_sort multi-sensor information ensemble-based automatic parking system for vehicle parallel/nonparallel initial state
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037424/
https://www.ncbi.nlm.nih.gov/pubmed/33804891
http://dx.doi.org/10.3390/s21072261
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