Developing a Test to Measure Distraction Potential of In-Vehicle Information System Tasksin Production Vehicles

摘要: Three experiments were conducted to assess a test of distraction potential for in-vehicle information systems (IVIS) and portable devices used while driving. The low-fidelity (PC-based) driving simulator; sensors record drivers’ control inputs in stationary production vehicles. Participants performed car-following target detection together with secondary tasks. Experiment 1 examined the effects two levels task (car-following) difficulty tasks on sensitivity. Detection included head-mounted (HDT) computer-generated multiple-target (MDT), which incorporated simple targets into simulated roadway display. Secondary (Circles) complex (navigation destination entry) visual-manual hands-free auditory-vocal (N-back). MDT was more sensitive load differences, HDT created problems eye tracker. Increasing had no effect metric disruptive than or task. second experiment compared metrics provided by occlusion paradigms: (1) traditional occlusion, involves intermittent masking simulate visual demands driving, (2) Enhanced Occlusion Task (EOT), added auditory tracking realistically demands. duration estimates EOT closer static completion times those obtained occlusion; however their usefulness estimating requires stronger connection comparable from protocol. did not improve R (task resumability) metric, although there independent evidence support expectation differences this metric. related performance degradation. Auditory paradigm revealed degradation consistent observed simulator metrics. 3 simulator-based navigation three functionality, including one original equipment manufacturer (OEM) systems, been independently rated as having different usability. Metrics strong between alone (car-following coherence, response time, proportion long glances) (simple complex) across all systems. Two (standard deviation lane position [SDLP] correct) exhibited significant Systems x interactions; It concluded that developing is feasible. Core include conditions (SDLP, delay, time) correct responses). Measures based data, primarily glances away forward roadway, promise. Estimates can be combined compute exposure risk.