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Methodology to investigate interference using off-the-shelf LiDARs

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Robinson, Jonathan, Venturi, Alberto, Dudley, Richard, Bevilacqua, Maurizio and Donzella, Valentina (2022) Methodology to investigate interference using off-the-shelf LiDARs. In: 2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI 2022), Singapore, 9-11 Dec 2022 (In Press)

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Abstract

With the increase of assisted and automated functions provided on new vehicles and some automotive manufacturers starting to equip high end vehicles with LiDARs, there is a need to consider and analyse the effects of having LiDAR sensors on different vehicles interacting with each other in close proximity (e.g. cities, highways, crossroads, etc.). This paper investigates interference between 360 degree scanning LiDARs, which are one of the common typologies of automotive LiDARs. One LiDAR was selected as the victim, and 5 different LiDARs were used one by one as offenders. The victim and offending LiDARs were placed in a controlled environment to reduce sources of noise, and several sets of measurements were carried out and repeated at least four times. When the attacker and victim LiDARs were turned on at the same time some variations in the signals were observed, however the statistical variation was too low to be able to identify interference. As a result, this work highlights that there is no obvious effect of interference witnessed between the selected off-the-shelf 360 degree LiDAR sensors; this lack of interference can be attributed to the working principle of this type of LiDAR and low probability of having directly interfering beams, and also to the focusing and filtering optical circuits that the LiDARs have by design. The presented results confirm that mechanical scanning LiDAR can be used safely for assisted and automated driving even in situations with multiple LiDARs.

Item Type: Conference Item (Paper)
Subjects: 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): Optical radar , Detectors, Automated vehicles , Interference (Aerodynamics) , Intelligent sensors
Publisher: IEEE
Official Date: 2022
Dates:
DateEvent
2022Available
1 September 2022Accepted
Status: Peer Reviewed
Publication Status: In Press
Reuse Statement (publisher, data, author rights): © 2022 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
Date of first compliant deposit: 13 October 2022
Date of first compliant Open Access: 14 October 2022
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDRoyal Academy of Engineeringhttp://dx.doi.org/10.13039/501100000287
UNSPECIFIEDHVM CATAPULThttps://hvm.catapult.org.uk/
UNSPECIFIEDDepartment for Business, Energy and Industrial Strategyhttp://dx.doi.org/10.13039/100011693
Conference Paper Type: Paper
Title of Event: 2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI 2022)
Type of Event: Conference
Location of Event: Singapore
Date(s) of Event: 9-11 Dec 2022
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