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Towards Safe and Sustainable Autonomous Vehicles Using Environmentally-Friendly Criticality Metrics

Jurj, Sorin Liviu and Werner, Tino and Grundt, Dominik and Hagemann, Willem and Möhlmann, Eike (2022) Towards Safe and Sustainable Autonomous Vehicles Using Environmentally-Friendly Criticality Metrics. Sustainability, 14 (12). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/su14126988. ISSN 2071-1050.

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Official URL: https://www.mdpi.com/2071-1050/15/10/7791


This paper presents a mathematical analysis of several criticality metrics used for evaluating the safety of autonomous vehicles (AVs) and also proposes novel environmentally-friendly metrics with the scope of facilitating their selection by future researchers who want to evaluate both safety and the environmental impact of AVs. Regarding this, first, we investigate whether the criticality metrics which are used to quantify the severeness of critical situations in autonomous driving are well-defined and work as intended. In some cases, the well-definedness or the intendedness of the metrics will be apparent, but in other cases, we will present mathematical demonstrations of these properties as well as alternative novel formulas. Additionally, we also present details regarding optimality. Secondly, we propose several novel environmentally-friendly metrics as well as a novel environmentally-friendly criticality metric that combines the safety and environmental impact in a car-following scenario. Third, we discuss the possibility of applying these criticality metrics in artificial intelligence (AI) training such as reinforcement learning (RL) where they can be used as penalty terms such as negative reward components. Finally, we propose a way to apply some of the metrics in a simple car-following scenario and show in our simulation that AVs powered by petrol emitted the most carbon emissions (54.92 g of CO2), being followed closely by diesel-powered AVs (54.67 g of CO2) and then by grid-electricity-powered AVs (31.16 g of CO2). Meanwhile, the AVs powered by electricity from a green source, such as solar energy, had 0 g of CO2 emissions, encouraging future researchers and the industry to develop more actively sustainable methods and metrics for powering and evaluating the safety and environmental impact of AVs using green energy.

Item URL in elib:https://elib.dlr.de/188075/
Document Type:Article
Title:Towards Safe and Sustainable Autonomous Vehicles Using Environmentally-Friendly Criticality Metrics
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Jurj, Sorin LiviuUNSPECIFIEDhttps://orcid.org/0000-0002-2689-6015UNSPECIFIED
Werner, TinoUNSPECIFIEDhttps://orcid.org/0000-0002-3512-8667UNSPECIFIED
Grundt, DominikUNSPECIFIEDhttps://orcid.org/0000-0002-8233-7429UNSPECIFIED
Hagemann, WillemUNSPECIFIEDhttps://orcid.org/0000-0002-9138-8340UNSPECIFIED
Möhlmann, EikeUNSPECIFIEDhttps://orcid.org/0000-0003-3815-6353UNSPECIFIED
Date:7 June 2022
Journal or Publication Title:Sustainability
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:MDPI
Keywords:autonomous vehicles; criticality metrics; safety; sustainability
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - Transport und Klima (old)
Location: Oldenburg
Institutes and Institutions:Institute of Systems Engineering for Future Mobility > Systems Theory and Design
Deposited By: Jurj, Sorin Liviu
Deposited On:05 Sep 2022 15:09
Last Modified:11 Sep 2023 14:54

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