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Auflistung nach Autor:in "Neukum, Alexandra"

1 - 4 von 4
  • Konferenzbeitrag
    Determining maximum velocity for automated driving functions
    (Mensch und Computer 2015 – Workshopband, 2015) Naujoks, Frederik; Purucker, Christian; Neukum, Alexandra
  • Konferenzbeitrag
    Specificity and timing of advisory warnings based on cooperative perception
    (Mensch & Computer 2014 - Workshopband, 2014) Naujoks, Frederik; Neukum, Alexandra
    Future perception and communication technologies provide the possibility of assisting drivers by so-called advisory warnings in potentially dangerous driving situations. The effectiveness of such advisory warnings will possibly depend on (1) timing (i.e., time left for avoiding the collision, when the driver is warned) and (2) the specificity of the warnings (i.e., warning content, for example information about the direction from which a hazard is imminent). Using a fixed-based driving simulator, n=21 participants encountered three different conflict situations: a longitudinal (pedestrian entering the road between parked cars), a crossing-path (crossing cyclist at an intersection) and a turning vehicle scenario (vehicle turning at an intersection and taking the driver´s right of way). Advisory warnings about upcoming conflicts were provided via Head-Up Display and accompanied by an unobtrusive acoustic signal. Warning timing (latest possible warning timing t0 vs. two seconds before t0+2s) and warning specificity (depiction of type and/or heading of road user vs. no depiction) were varied. Effects on driving behavior and situation criticality were strongly dependent on warning timing, with early warnings (t0+2s) being more effective than late warnings (t0). In comparison to warning timing, the effects of warning specificity were of minor importance to driving behavior, but had a great impact on ratings of usefulness.
  • Konferenzbeitrag
    Speech improves human-automation cooperation in automated driving
    (Mensch und Computer 2016 – Workshopband, 2016) Naujoks, Frederik; Forster, Yannick; Wiedemann, Katharina; Neukum, Alexandra
    During highly automated driving, upcoming automated manoeuvres (e.g., lane changes) should be communicated to the driver in order to ensure system transparency. As driving time can be used for non-driving-related tasks (NDRT), such as office work or in-vehicle entertainment, drivers might prefer to be informed in a non-distracting way as interruptions of ongoing NDRTs may be perceived as a nuisance (e.g., when drivers are required to retrieve information from attention demanding displays). In this paper, the potential for using speech output to improve human-automation communication is explored. A sample of 17 drivers participated in a simulated automated driving experience in a motion-based driving simulator, which replicated different situations for the participants that required communication between the automation and the driver (e.g., lane changes, avoiding of obstacles). Compared to generic auditory output (i.e., standard information tones), communicating upcoming automated manoeuvres by speech led to a decrease in self-reported visual workload and reduced interference with NDRTs. Participants clearly favoured the speech-based output.
  • Konferenzbeitrag
    Vorhersage von Blickabwendungszeiten mit Keystroke-Level-Modeling
    (Mensch & Computer 2014 - Workshopband, 2014) Purucker, Christian; Naujoks, Frederik; Prill, Andy; Krause, Thomas; Neukum, Alexandra