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Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations
Cooperative perception, or collective perception (CP), is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to share its local perception information with others by means of vehicle-to-X (V2X) communication, thereby achieving improve...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794841/ https://www.ncbi.nlm.nih.gov/pubmed/33396804 http://dx.doi.org/10.3390/s21010200 |
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author | Shan, Mao Narula, Karan Wong, Yung Fei Worrall, Stewart Khan, Malik Alexander, Paul Nebot, Eduardo |
author_facet | Shan, Mao Narula, Karan Wong, Yung Fei Worrall, Stewart Khan, Malik Alexander, Paul Nebot, Eduardo |
author_sort | Shan, Mao |
collection | PubMed |
description | Cooperative perception, or collective perception (CP), is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to share its local perception information with others by means of vehicle-to-X (V2X) communication, thereby achieving improved efficiency and safety in road transportation. In this paper, we present our recent progress on the development of a connected and automated vehicle (CAV) and intelligent roadside unit (IRSU). The main contribution of the work lies in investigating and demonstrating the use of CP service within intelligent infrastructure to improve awareness of vulnerable road users (VRU) and thus safety for CAVs in various traffic scenarios. We demonstrate in experiments that a connected vehicle (CV) can “see” a pedestrian around the corners. More importantly, we demonstrate how CAVs can autonomously and safely interact with walking and running pedestrians, relying only on the CP information from the IRSU through vehicle-to-infrastructure (V2I) communication. This is one of the first demonstrations of urban vehicle automation using only CP information. We also address in the paper the handling of collective perception messages (CPMs) received from the IRSU, and passing them through a pipeline of CP information coordinate transformation with uncertainty, multiple road user tracking, and eventually path planning/decision-making within the CAV. The experimental results were obtained with manually driven CV, fully autonomous CAV, and an IRSU retrofitted with vision and laser sensors and a road user tracking system. |
format | Online Article Text |
id | pubmed-7794841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77948412021-01-10 Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations Shan, Mao Narula, Karan Wong, Yung Fei Worrall, Stewart Khan, Malik Alexander, Paul Nebot, Eduardo Sensors (Basel) Article Cooperative perception, or collective perception (CP), is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to share its local perception information with others by means of vehicle-to-X (V2X) communication, thereby achieving improved efficiency and safety in road transportation. In this paper, we present our recent progress on the development of a connected and automated vehicle (CAV) and intelligent roadside unit (IRSU). The main contribution of the work lies in investigating and demonstrating the use of CP service within intelligent infrastructure to improve awareness of vulnerable road users (VRU) and thus safety for CAVs in various traffic scenarios. We demonstrate in experiments that a connected vehicle (CV) can “see” a pedestrian around the corners. More importantly, we demonstrate how CAVs can autonomously and safely interact with walking and running pedestrians, relying only on the CP information from the IRSU through vehicle-to-infrastructure (V2I) communication. This is one of the first demonstrations of urban vehicle automation using only CP information. We also address in the paper the handling of collective perception messages (CPMs) received from the IRSU, and passing them through a pipeline of CP information coordinate transformation with uncertainty, multiple road user tracking, and eventually path planning/decision-making within the CAV. The experimental results were obtained with manually driven CV, fully autonomous CAV, and an IRSU retrofitted with vision and laser sensors and a road user tracking system. MDPI 2020-12-30 /pmc/articles/PMC7794841/ /pubmed/33396804 http://dx.doi.org/10.3390/s21010200 Text en © 2020 by the authors. 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/). |
spellingShingle | Article Shan, Mao Narula, Karan Wong, Yung Fei Worrall, Stewart Khan, Malik Alexander, Paul Nebot, Eduardo Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations |
title | Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations |
title_full | Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations |
title_fullStr | Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations |
title_full_unstemmed | Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations |
title_short | Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations |
title_sort | demonstrations of cooperative perception: safety and robustness in connected and automated vehicle operations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794841/ https://www.ncbi.nlm.nih.gov/pubmed/33396804 http://dx.doi.org/10.3390/s21010200 |
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