elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Impressum | Datenschutz | Kontakt | English
Schriftgröße: [-] Text [+]

Numerical Crash Analyses of Underrepresented Populations in Autonomous Vehicles

Kannan, Vishnuvel und Harrison, Andrew und Sturm, Ralf (2024) Numerical Crash Analyses of Underrepresented Populations in Autonomous Vehicles. Masterarbeit, Universität Stuttgart.

[img] PDF - Nur DLR-intern zugänglich
22MB

Kurzfassung

This thesis conducts a thorough analysis to better understand the safety concerns associated with the deployment of autonomous vehicles (AVs) on our roads. It hopes to highlight important issues that are frequently disregarded in the discourse at large. As autonomous vehicle technology develops, it is critical to acknowledge that the transitional period, during which AVs coexist with conventional vehicles, presents a special set of difficulties, main among them being safety. Research on various interior configurations for Autonomous Vehicles (AVs) with the goal of improving comfort and supporting flexible seating arrangements is a key area of interest. However, this divergence from conventional vehicle designs raises important safety issues, particularly with regard to the lack of components meant to reduce the likelihood of injuries, like foot and knee supports. To address and mitigate these safety concerns, a great deal of literature research is carefully done, guaranteeing that innovations in AV design put passenger safety first. This study highlights the underrepresentation of females and individuals with disabilities in existing research, signaling a crucial area for future investigation and development. It highlights not only how important it is to welcome diverse populations but also how important it is to establish an atmosphere in which every person, regardless of gender or ability, is given equal weight in the development of Autonomous Vehicle (AV) technology. In addition to that, the benefits of using HBMs over ATDs for such diverse populations and for safety valuation are addressed.

elib-URL des Eintrags:https://elib.dlr.de/204949/
Dokumentart:Hochschulschrift (Masterarbeit)
Titel:Numerical Crash Analyses of Underrepresented Populations in Autonomous Vehicles
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Kannan, VishnuvelNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Harrison, AndrewAndrew.Harrison (at) dlr.dehttps://orcid.org/0000-0003-2122-0697NICHT SPEZIFIZIERT
Sturm, RalfRalf.Sturm (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Mai 2024
Open Access:Nein
Seitenanzahl:71
Status:veröffentlicht
Stichwörter:Human Modelling, Menschmodell, Crash, Autonomous Vehicle, Interior
Institution:Universität Stuttgart
Abteilung:Insitute of enginieering and computational mechanics
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Straßenverkehr
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V ST Straßenverkehr
DLR - Teilgebiet (Projekt, Vorhaben):V - V&V4NGC - Methoden, Prozesse und Werkzeugketten für die Validierung & Verifikation von NGC
Standort: Stuttgart
Institute & Einrichtungen:Institut für Fahrzeugkonzepte > Fahrzeugarchitekturen und Leichtbaukonzepte
Hinterlegt von: Sturm, Ralf
Hinterlegt am:24 Jun 2024 07:58
Letzte Änderung:24 Jun 2024 07:58

Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags

Blättern
Suchen
Hilfe & Kontakt
Informationen
electronic library verwendet EPrints 3.3.12
Gestaltung Webseite und Datenbank: Copyright © Deutsches Zentrum für Luft- und Raumfahrt (DLR). Alle Rechte vorbehalten.