Literature DB >> 33396804

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

Mao Shan1, Karan Narula1, Yung Fei Wong2, Stewart Worrall1, Malik Khan2, Paul Alexander2, Eduardo Nebot1.   

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 "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.

Entities:  

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

Year:  2020        PMID: 33396804     DOI: 10.3390/s21010200

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Analysis of Cooperative Perception in Ant Traffic and Its Effects on Transportation System by Using a Congestion-Free Ant-Trail Model.

Authors:  Prafull Kasture; Hidekazu Nishimura
Journal:  Sensors (Basel)       Date:  2021-03-30       Impact factor: 3.576

  1 in total

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