@article{ref1,
title="Demonstrations of cooperative perception: safety and robustness in connected and automated vehicle operations",
journal="Sensors (Basel)",
year="2021",
author="Nebot, Eduardo and Alexander, Paul and Khan, Malik and Worrall, Stewart and Wong, Yung Fei and Narula, Karan and Shan, Mao",
volume="21",
number="1",
pages="e200-e200",
abstract="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 &quot;see&quot; 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.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s21010200",
url="http://dx.doi.org/10.3390/s21010200"
}