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

Jurj, Sorin Liviu und Werner, Tino und Grundt, Dominik und Hagemann, Willem und 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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Offizielle URL: https://www.mdpi.com/2071-1050/15/10/7791

Kurzfassung

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.

elib-URL des Eintrags:https://elib.dlr.de/188075/
Dokumentart:Zeitschriftenbeitrag
Titel:Towards Safe and Sustainable Autonomous Vehicles Using Environmentally-Friendly Criticality Metrics
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Jurj, Sorin Liviusorin.jurj (at) dlr.dehttps://orcid.org/0000-0002-2689-6015NICHT SPEZIFIZIERT
Werner, Tinotino.werner (at) dlr.dehttps://orcid.org/0000-0002-3512-8667NICHT SPEZIFIZIERT
Grundt, Dominikdominik.grundt (at) dlr.dehttps://orcid.org/0000-0002-8233-7429NICHT SPEZIFIZIERT
Hagemann, Willemwillem.hagemann (at) dlr.dehttps://orcid.org/0000-0002-9138-8340NICHT SPEZIFIZIERT
Möhlmann, Eikeeike.moehlmann (at) dlr.dehttps://orcid.org/0000-0003-3815-6353NICHT SPEZIFIZIERT
Datum:7 Juni 2022
Erschienen in:Sustainability
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:14
DOI:10.3390/su14126988
Verlag:Multidisciplinary Digital Publishing Institute (MDPI)
Name der Reihe:MDPI
ISSN:2071-1050
Status:veröffentlicht
Stichwörter:autonomous vehicles; criticality metrics; safety; sustainability
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Verkehrssystem
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V VS - Verkehrssystem
DLR - Teilgebiet (Projekt, Vorhaben):V - Transport und Klima (alt)
Standort: Oldenburg
Institute & Einrichtungen:Institut für Systems Engineering für zukünftige Mobilität > Systems Theory and Design
Hinterlegt von: Jurj, Sorin Liviu
Hinterlegt am:05 Sep 2022 15:09
Letzte Änderung:11 Sep 2023 14:54

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