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

Schrank, Andreas Gottfried and Wendorff, Nils and 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.

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

Abstract

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.

Item URL in elib:https://elib.dlr.de/204919/
Document Type:Conference or Workshop Item (Poster)
Title:Assisting the Remote Assistant: Augmenting Degraded Video Streams with Additional Sensor Data to Improve Situation Awareness in Complex Urban Traffic
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Schrank, Andreas GottfriedUNSPECIFIEDhttps://orcid.org/0000-0001-8352-1052UNSPECIFIED
Wendorff, NilsUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Oehl, MichaelUNSPECIFIEDhttps://orcid.org/0000-0002-0871-2286UNSPECIFIED
Date:8 June 2024
Journal or Publication Title:Communications in Computer and Information Science
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Volume:2118
DOI:10.1007/978-3-031-61963-2_28
Series Name:Communications in Computer and Information Science (CCIS)
ISSN:1865-0929
Status:Published
Keywords:Remote operation remote assistance human-machine interaction highly automated vehicles
Event Title:26th International Conference on Human-Machine Interaction (HCII 2024)
Event Location:Washington, DC, USA
Event Type:international Conference
Event Start Date:29 June 2024
Event End Date:4 July 2024
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Cooperative Systems, BS
Deposited By: Schrank, Andreas Gottfried
Deposited On:01 Jul 2024 09:23
Last Modified:01 Jul 2024 09:23

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