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

Assisting the Remote Assistant: Augmenting Degraded Video Streams with Additional Sensor Data to Improve Situation Awareness in Complex Urban Traffic

Schrank, Andreas Gottfried und Wendorff, Nils und Oehl, Michael (2024) Assisting the Remote Assistant: Augmenting Degraded Video Streams with Additional Sensor Data to Improve Situation Awareness in Complex Urban Traffic. In: Communications in Computer and Information Science, 2118. 26th International Conference on Human-Machine Interaction (HCII 2024), 2024-06-29 - 2024-07-04, Washington, DC, USA. doi: 10.1007/978-3-031-61963-2_28. ISSN 1865-0929.

Dieses Archiv kann nicht den Volltext zur Verfügung stellen.

Offizielle URL: https://link.springer.com/chapter/10.1007/978-3-031-61963-2_28

Kurzfassung

Remotely operating highly automated vehicles (HAVs, SAE 4 [1]) bears the potential to boost their large-scale deployment. A human operator supports the vehicle automation remotely in situations that exceed the automation’s capabilities. A high-quality video stream displaying the HAV’s environment is key for the remote operator to obtain and maintain situation awareness. One of the major technical obstacles is the frequent and serious limitation of connectivity between the remote operator and the HAV, particularly a drop of bandwidth. This results in a severely degraded video resolution. As a remedy, we propose the use of data transmitted from the HAV’s additional onboard sensors to augment a low-resolution video stream. A significantly lower bandwidth suffices to transmit sensor compared to video data, enabling their transmission even when the video resolution is degraded. This could help the remote operator gain situation awareness, particularly in remote assistance, a variant of remote operation in which the operator provides high-level advice to the vehicle [2]. To confirm the need for a sensor data augmented view of the traffic situation, an experimental online user study (N = 117) was conducted. The study presented short video clips of complex naturalistic urban road traffic to participants. The objective was to examine if overlaying the video stream with visualized sensor data improves a remote assistant’s situation awareness and whether the effect of overlaid sensor data depends on the video resolution. Results revealed a significant effect of video resolution on objective situation awareness. Additionally, an interaction effect between resolution and sensor-data overlay became evident on the perception level of situation awareness. Hence, sensor data augmentation of degraded video streams may support the remote assistant’s situation awareness by increasing the salience of relevant elements in a traffic situation. Future research will investigate sensor data augmentation in a standardized simulation environment.

elib-URL des Eintrags:https://elib.dlr.de/204919/
Dokumentart:Konferenzbeitrag (Poster)
Titel:Assisting the Remote Assistant: Augmenting Degraded Video Streams with Additional Sensor Data to Improve Situation Awareness in Complex Urban Traffic
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Schrank, Andreas GottfriedAndreas.Schrank (at) dlr.dehttps://orcid.org/0000-0001-8352-1052NICHT SPEZIFIZIERT
Wendorff, NilsNils.Wendorff (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Oehl, MichaelMichael.Oehl (at) dlr.dehttps://orcid.org/0000-0002-0871-2286NICHT SPEZIFIZIERT
Datum:8 Juni 2024
Erschienen in:Communications in Computer and Information Science
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
Band:2118
DOI:10.1007/978-3-031-61963-2_28
Name der Reihe:Communications in Computer and Information Science (CCIS)
ISSN:1865-0929
Status:veröffentlicht
Stichwörter:Remote operation remote assistance human-machine interaction highly automated vehicles
Veranstaltungstitel:26th International Conference on Human-Machine Interaction (HCII 2024)
Veranstaltungsort:Washington, DC, USA
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:29 Juni 2024
Veranstaltungsende:4 Juli 2024
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 - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz
Standort: Braunschweig
Institute & Einrichtungen:Institut für Verkehrssystemtechnik > Kooperative Systeme, BS
Hinterlegt von: Schrank, Andreas Gottfried
Hinterlegt am:01 Jul 2024 09:23
Letzte Änderung:01 Jul 2024 09:23

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.