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Realistic LiDAR with noise model for real-time testing of automated vehicles in a virtual environment final

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Espineira, Juan, Robinson, Jonathan, Groenewald, Jakobus, Chan, Pak Hung and Donzella, Valentina (2021) Realistic LiDAR with noise model for real-time testing of automated vehicles in a virtual environment final. Sensors Journal . pp. 1-8. doi:10.1109/JSEN.2021.3059310 ISSN 1558-1748.

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Official URL: https://doi.org/10.1109/JSEN.2021.3059310

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Abstract

The global Connected and Autonomous Mobility industry is growing at a rapid pace. To ensure the successful adoption of connected automated mobility solutions, their safety, reliability and hence the public acceptance are paramount. It is widely known that in order to demonstrate that L3+ automated systems are safer with respect to human drivers, upwards of several millions of miles need to be driven. The only way to efficiently achieve this amount of tests in a timely manner is by using simulations and high fidelity virtual environments. Two key components of being able to test an automated system in a synthetic environment are validated sensor models and noise models for each sensor technology. In fact, the sensors are the element feeding information into the system in order to enable it to safely plan the trajectory and navigate. In this paper, we propose an innovative real-time LiDAR sensor model based on beam propagation and a probabilistic rain model, taking into account raindrop distribution and size. The model can seamlessly run in real-time, synchronised with the visual rendering, in immersive driving simulators, such as the WMG 3xD simulator. The models are developed using Unreal engine, therefore demonstrating that gaming technology can be merged with the Automated Vehicles (AVs) simulation toolchain for the creation and visualization of high fidelity scenarios and for AV accurate testing. This work can be extended to add more sensors and more noise factors or cyberattacks in real-time simulations.

Item Type: Journal Article
Subjects: T Technology > TE Highway engineering. Roads and pavements
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Divisions: Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Automated vehicles , Optical radar , Intelligent transportation systems, Automotive sensors
Journal or Publication Title: Sensors Journal
Publisher: IEEE
ISSN: 1558-1748
Official Date: 12 February 2021
Dates:
DateEvent
12 February 2021Published
2 February 2021Accepted
Page Range: pp. 1-8
DOI: 10.1109/JSEN.2021.3059310
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version: Restricted or Subscription Access
Copyright Holders: IEEE
Date of first compliant deposit: 15 February 2021
Date of first compliant Open Access: 16 February 2021
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDInnovate UKhttp://dx.doi.org/10.13039/501100006041
UNSPECIFIEDRoyal Academy of Engineeringhttp://dx.doi.org/10.13039/501100000287

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