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Entwicklung und Validierung einer Fahrsimulationsumgebung für Interface-Testing im Kontext Elektromobilität

  • March 2019
DOI:10.13140/RG.2.2.26178.32962/1
  • Conference: 3. Kongress der Fachgruppe Verkehrspsychologie, Saarbrücken, 5.-7.03.2019
Authors:
Lukas Bernhardt at Universität zu Lübeck
Lukas Bernhardt
Vivien Moll at Universität zu Lübeck
Vivien Moll
Thomas Franke at Universität zu Lübeck
Thomas Franke
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Abstract

Bisherige Forschung hat gezeigt, dass die Art und Weise, wie Informationen über Energieverbräuche wahrgenommen und verarbeitet werden, einen bedeutenden Einfluss auf die Energieeffizienz der Fahrweise von Fahrern hat. Die optimale Gestaltung von Energie-Interfaces ist daher ein zentraler Bereich im Design von Nutzerschnittstellen im Fahrzeugkontext. Neue Interface-Möglichkeiten durch mobile Displays sowie Trends wie Elektrifizierung und Automatisierung stellen hierbei neue Designherausforderungen dar. In diesem Rahmen werden effiziente Testverfahren von neuen Fahrzeuganzeigen auf Usability und Verhaltenswirksamkeit immer wichtiger. Mit dem IMIS-Fahrsimulator wird eine Testumgebung für Nutzerstudien zu neuen Fahrzeuginterfaces in Elektrofahrzeugen entwickelt. Ziel ist es, mittels Anpassungen der Software BeamNG.research und der entsprechenden Hardware die Fahrsimulationsumgebung an ein reales Fahrzeug anzunähern, um eine möglichst realistische Fahrsimulation zu realisieren. Hierfür werden nicht nur ein Elektrofahrzeug mit angepasstem Energiemodell integriert, sondern auch eine Anpassung an die Maße eines realen Fahrzeugs, z. B. hinsichtlich Sitzposition und Lenkradwinkel, vorgenommen. Die Anpassungen werden in einer Nutzerstudie validiert und erste Ergebnisse aus den Validierungsstudien präsentiert.
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Autoren
Vivien Moll
Doktorandin Ingenieurpsychologie, Nutzer-Energie-Interaktion
Thomas Franke
Professor für Ingenieurpsychologie und Kognitive Ergonomie
References
[1] Jamson, S.L., Hibberd, D.L., & Jamson, A.H. (2015). Drivers’ ability to learn eco-driving skills; effects on fuel efficient and safe driving behaviour. Transport. Res. Part C, 58, 657-668.
[2] Pampel, S.M., Jamson, S.L., Hibberd, D.L., & Barnard, Y. (2015). How I reduce fuel consumption: An experimental study on mental models of eco-driving. Transport. Res. Part C, 58, 669-680.
[3] Pampel, S. M., Jamson, S. L., Hibberd, D., & Barnard, Y. (2017). The activation of eco-driving mental models: Can text messages prime drivers to use their existing knowledge and skills? Cogn Tech
Work, 19, 743-758.
[4] Makransky, G., Lilleholt, L., & Aaby, A. (2017). Development and validation of the Multimodal Presence Scale for virtual reality environments: A confirmatory factor analysis and item response
theory approach. Computers in Human Behavior, 72, 276-285.
[5] Volkmann, T., Wessel, D., Jochems, N., Franke, T. (2018). German Translation of the Multimodal Presence Scale. Mensch und Computer 2018 –Tagungsband.
Erste Ergebnisse
Nächste Schritte
Erste Validierung
N = 22 (20 weiblich), Alter: M= 23.8 Jahre (SD = 5.9)
Fahrerfahrung: M = 6.4 Jahre (SD = 5.8)
M = 74,685 km (SD = 208,223 km)
Ausführen von verschiedenen Beschleunigungs- und Brems-
manövern zwischen 0 km/h und 100 km/h über 50-70 min.
Erfassung der Physical Presence (MPS-Skala…) [4]
Erfassung spezifische Aspekte Fahrgefühl (Likert-Skala 1-6)
„Die/Das …. war wie in einem echten Auto“
•Fahrsimulatorstudien eignen sich gut zur Beurteilung von
Fahrerassistenzsystemen und zur Evaluation von Anzeigen-/
Bedienkonzepten, auch im Bereich Ecodriving [1, 2, 3]
•Ziel: Entwicklung einer Fahrsimulationsumgebung zur
Untersuchung von energieeffizientem Fahrverhalten und
Entwicklung von Energie-Interfaces
•Zentrale Herausforderung: Bestmögliche Annäherung der
Simulation an reale Bedingungen
(1) Annäherung an reales E-Fahrzeug (Renault ZOE)
Abmessungen, Sitzposition, Pedalwinkel, Sichtfeld, …
(2) Integration eines validen Energiemodells in die Simulation
(3) Entwurf einer Toolbox für Energie-Interfaces
•Setup:
−180°-Fahrsimulator (3x55 Zoll LCD)
−Verstellbarer Fahrersitz (adaptierte RSeat RS1 Plattform)
−Fahrzeugsteuerung mit Force Feedback (Fanatec)
−Integration Renault ZOE Lenkrad
Zwischenfazit: Solide erste Ergebnisse mit Ausbaupotenzial
IMIS-Fahrsimulator
Entwicklung und Validierung
einer Fahrsimulationsumgebung
für Interface-Testing
im Kontext Elektromobilität
Lukas Bernhardt, Vivien Moll, Thomas Franke
Institut für Multimediale und Interaktive Systeme (IMIS)
Ingenieurpsychologie und Kognitive Ergonomie
Universität zu Lübeck
Weiterentwicklung der Fahrsimulationsumgebung
•Weitere Schritte der Validierung:
−Direktvergleich & Angleichung ZOE vs. Fahrsimulator
−Abmessungen, Pedalwiderstände und Pedalkennlinien,
Lenkradkennlinie vermessen & angleichen
•Weitere Schritte bzgl. Hard- und Software:
−Integration Armaturenbrett (inkl. Displaypositionen etc.)
−Verbesserung der Geschwindigkeitswahrnehmung
Fahrerlebnis & Fahrgefühl
Lukas Bernhardt
Bachelorand Medieninformatik, Fahrsimulatorvalidierung
(1) Physical Presence:
Wahrgenommener Physical Presence Score: M = 3.26 (SD = 0.45)
(Referenzwert: einfache VR-Anwendung [5] M = 3.15-3.54)
(2) Spezifisches Fahrgefühl:
Sitzgefühl: M = 3.45 (P25 = 3.00; P75 = 4.00)
Sitzposition: M = 3.55 (P25 = 3.00; P75 = 4.00)
Dosierbarkeit Fahrpedal: M = 3.36 (P25 = 2.25; P75 = 4.00)
Dosierbarkeit Bremspedal: M = 3.82 (P25 = 3.00; P75 = 4.75)
Güte Lenkradsteuerung: M = 3.00 (P25 = 2.00; P75 = 4.00)
… wie in einem echten Auto.
(Abstände/Positionen)
ResearchGate has not been able to resolve any citations for this publication.
The activation of eco-driving mental models: Can text messages prime drivers to use their existing knowledge and skills?
Article
Full-text available
Eco-driving campaigns have traditionally assumed that drivers lack the necessary knowledge and skills and that this is something that needs rectifying. Therefore, many support systems have been designed to closely guide drivers and fine-tune their proficiency. However, research suggests that drivers already possess a substantial amount of the necessary knowledge and skills regarding eco-driving. In previous studies, participants used these effectively when they were explicitly asked to drive fuel-efficiently. In contrast, they used their safe driving skills when they were instructed to drive as they would normally. Hence, it is assumed that many drivers choose not to engage purposefully in eco-driving in their everyday lives. The aim of the current study was to investigate the effect of simple, periodic text messages (nine messages in 2 weeks) on drivers’ eco- and safe driving performance. It was hypothesised that provision of eco-driving primes and advice would encourage the activation of their eco-driving mental models and that comparable safety primes increase driving safety. For this purpose, a driving simulator experiment was conducted. All participants performed a pre-test drive and were then randomly divided into four groups, which received different interventions. For a period of 2 weeks, one group received text messages with eco-driving primes and another group received safety primes. A third group received advice messages on how to eco-drive. The fourth group were instructed by the experimenter to drive fuel-efficiently, immediately before driving, with no text message intervention. A post-test drive measured behavioural changes in scenarios deemed relevant to eco- and safe driving. The results suggest that the eco-driving prime and advice text messages did not have the desired effect. In comparison, asking drivers to drive fuel-efficiently led to eco-driving behaviours. These outcomes demonstrate the difficulty in changing ingrained habits. Future research is needed to strengthen such messages or activate existing knowledge and skills in other ways, so driver behaviour can be changed in cost-efficient ways.
View
Development and Validation of the Multimodal Presence Scale for Virtual Reality Environments: A Confirmatory Factor Analysis and Item Response Theory Approach
Article
Full-text available
Presence is one of the most important psychological constructs for understanding human-computer interaction. However, different terminology and operationalizations of presence across fields have plagued the comparability and generalizability of results across studies. Lee’s (2004) unified understanding of presence as a multidimensional construct made up of physical, social, and self-presence, has created a unified theory of presence; nevertheless, there are still no psychometrically valid measurement instruments based on the theory. Two studies were conducted that describe the development of a standardized multidimensional measure of presence (the MPS) for a VR learning context based on this theory, and its validation using confirmatory factor analysis and item response theory. The results from Study 1 which included 161 medical students from Denmark indicated that the items used in the MPS measure a three dimensional theoretical model of presence: physical, social, and self-presence. Furthermore, IRT analyses indicated that it was possible to limit the number of items in the MPS to 15 (five items per sub-dimension) while maintaining the construct validity and reliability of the measure. The results of Study 2, which included 118 biology students from Scotland, supported the validity and generalizability of the MPS in a new context.
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How I reduce fuel consumption: An experimental study on mental models of eco-driving
Article
Eco-driving has the potential to reduce fuel consumption and therefore emissions considerably. Previous research suggests that drivers have a certain level of eco-driving knowledge and skills, which they refrain from practising in their everyday lives. At the same time misconceptions and ambiguous messages from eco-driving support systems can confuse and demotivate. This research aimed to identify the mental models of eco-driving that regular drivers have. A driving simulator experiment with a varied road layout comprising urban and motorway sections was designed. The study used simple driving task instructions to investigate changes in the participants’ behaviour and thoughts in three conditions. Sixteen drivers were asked to ‘Drive normally’, ‘Drive safely’ or ‘Drive fuel-efficiently’. Behavioural measures, think aloud protocols and interviews were compared and analysed. The emphasis of this study was on eco-driving relevant indicators such as accelerating, braking, coasting and car-following. The results show that the participants do have mental models of eco-driving, which they did not use in the Baseline drive, when they were instructed to ‘Drive normally’. Misconceptions about speed and travel time provide the potential for more effective communication with the driver about the momentary efficient speed as well as resulting time losses and fuel savings. In addition, in-vehicle guidance can increase driving safety compared to practicing eco-driving without them.
View
Drivers’ ability to learn eco-driving skills; effects on fuel efficient and safe driving behaviour
Article
Whilst driving is inherently a safety–critical task, awareness of fuel-efficient driving techniques has gained popularity in both the public and commercial domains. Green driving, whether motivated by financial or environmental savings, has the potential to reduce the production of greenhouse gases by a significant amount. This paper focusses on the interaction between the driver and their vehicle – what type of eco-driving information is easy to use and learn whilst not compromising safety. A simulator study evaluated both visual and haptic eco-driving feedback systems in the context of hill driving. The ability of drivers to accurately follow the advice, as well as their propensity to prioritise it over safe driving was investigated. We found that any type of eco-driving advice improved performance and whilst continuous real-time visual feedback proved to be the most effective, this modality obviously reduces attention to the forward view and increases subjective workload. On the other hand, the haptic force system had little effect on reported workload, but was less effective that the visual system. A compromise may be a hybrid system that adapts to drivers’ performance on an on-going basis.
View
German Translation of the Multimodal Presence Scale
  • Jan 2018
  • T Volkmann
  • D Wessel
  • N Jochems
  • T Franke
Volkmann, T., Wessel, D., Jochems, N., Franke, T. (2018). German Translation of the Multimodal Presence Scale. Mensch und Computer 2018 -Tagungsband.