Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations.

V2X communication collective perception collective perception service connected and automated vehicle cooperative perception intelligent roadside unit

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
30 Dec 2020
Historique:
received: 29 11 2020
revised: 21 12 2020
accepted: 24 12 2020
entrez: 5 1 2021
pubmed: 6 1 2021
medline: 6 1 2021
Statut: epublish

Résumé

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.

Identifiants

pubmed: 33396804
pii: s21010200
doi: 10.3390/s21010200
pmc: PMC7794841
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : iMOVE CRC
ID : iMOVE Project 1-006

Références

Sensors (Basel). 2020 Sep 17;20(18):
pubmed: 32957554

Auteurs

Mao Shan (M)

Australian Centre for Field Robotics, The University of Sydney, Sydney, NSW 2006, Australia.

Karan Narula (K)

Australian Centre for Field Robotics, The University of Sydney, Sydney, NSW 2006, Australia.

Yung Fei Wong (YF)

Cohda Wireless, 27 Greenhill Road, Wayville, SA 5034, Australia.

Stewart Worrall (S)

Australian Centre for Field Robotics, The University of Sydney, Sydney, NSW 2006, Australia.

Malik Khan (M)

Cohda Wireless, 27 Greenhill Road, Wayville, SA 5034, Australia.

Paul Alexander (P)

Cohda Wireless, 27 Greenhill Road, Wayville, SA 5034, Australia.

Eduardo Nebot (E)

Australian Centre for Field Robotics, The University of Sydney, Sydney, NSW 2006, Australia.

Classifications MeSH