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Validating simulation environments for automated driving systems using 3d object comparison metric
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Wallace, Albert, Khastgir, Siddartha, Zhang, Xizhe, Brewerton, Simon, Anctil, Benoit, Burns, Peter, Charlebois, Dominique and Jennings, Paul. A. (2022) Validating simulation environments for automated driving systems using 3d object comparison metric. In: 33rd IEEE Intelligent Vehicles Symposium, Aachen, Germany, 05-09 Jun 2022. Published in: 2022 IEEE Intelligent Vehicles Symposium (IV) ISBN 9781665488211. doi:10.1109/IV51971.2022.9827354
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WRAP-Validating-simulation-environments-for-automated-driving-systems-Khastgir-2022.pdf - Accepted Version - Requires a PDF viewer. Download (812Kb) | Preview |
Official URL: https://doi.org/10.1109/IV51971.2022.9827354
Abstract
One of the main challenges for the introduction of Automated Driving Systems (ADSs) is their verification and validation (V&V). Simulation based testing has been widely accepted as an essential aspect of the ADS V&V processes. Simulations are especially useful when exposing the ADS to challenging driving scenarios, as they offer a safe and efficient alternative to real world testing. It is thus suggested that evidence for the safety case for an ADS will include results from both simulation and real-world testing. However, for simulation results to be trusted as part of the safety case of an ADS for its safety assurance, it is essential to prove that the simulation results are representative of the real world, thus validating the simulation platform itself.
In this paper, we propose a novel methodology for validating the simulation environments focusing on comparing point cloud data from real lidar sensor and a simulated lidar sensor model. A 3D object dissimilarity metric is proposed to compare between the two maps (real and simulated), to quantify how accurate the simulation is. This metric is tested on collected lidar point cloud data and the simulated point cloud generated in the simulated environment.
Item Type: | Conference Item (Paper) | ||||||||||||
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Subjects: | 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, Automated vehicles -- Safety measures, Computer simulation | ||||||||||||
Journal or Publication Title: | 2022 IEEE Intelligent Vehicles Symposium (IV) | ||||||||||||
Publisher: | IEEE | ||||||||||||
ISBN: | 9781665488211 | ||||||||||||
Official Date: | 2022 | ||||||||||||
Dates: |
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DOI: | 10.1109/IV51971.2022.9827354 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
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. | ||||||||||||
Copyright Holders: | IEEE | ||||||||||||
Date of first compliant deposit: | 19 April 2022 | ||||||||||||
Date of first compliant Open Access: | 21 April 2022 | ||||||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | ||||||||||||
Title of Event: | 33rd IEEE Intelligent Vehicles Symposium | ||||||||||||
Type of Event: | Conference | ||||||||||||
Location of Event: | Aachen, Germany | ||||||||||||
Date(s) of Event: | 05-09 Jun 2022 | ||||||||||||
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