Modeling the effects of perceived intuitiveness and urgency of various auditory warnings on driver takeover performance in automated vehicles |
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| Institution: | 1. Grado Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, USA;2. Department of Industrial and Manufacturing Engineering, Pennsylvania State University, USA;1. Academy of Professional Studies Sumadija, Department in Kragujevac, Kosovska 8, 34000 Kragujevac, Serbia;2. University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia;3. P.E. GSP Belgrade, Knjeginje Ljubice 29, 11000 Belgrade, Serbia;4. University of Montenegro, Faculty of Mechanical Engineering, Blv. Dzordza Vasingtona bb, 81000 Podgorica, Montenegro;1. Civil Aviation University of China, Tianjin 300300, PR China;2. Beijing University of Technology, Beijing 100124, PR China;1. Department of Cognitive Robotics, Faculty Mechanical, Maritime and Materials Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, the Netherlands;2. Group Renault, Chassis Systems Department, 1 Avenue du Golf, 78280 Guyancourt, France;3. Department of Computer and System Engineering/U2IS, ENSTA Paris, Institut Polytechnique de Paris, 828 Boulevard des Maréchaux, 91762 Palaiseau Cedex, France;1. Robert Bosch GmbH, Gerlingen-Schillerhöhe, Germany;2. Assessment and Intervention, Faculty of Psychology, TU Dresden, Germany;1. UNICAEN, INSERM, COMETE, GIP CYCERON, Normandie University, 14000 Caen, France;2. UNICAEN, CNRS, LMNO, Normandie University, 14000 Caen, France;3. UNICAEN, ENSICAEN, LAC, Normandie University, 14000 Caen, France;4. UNICAEN, EPHE Paris, INSERM, NIMH, GIP Cyceron, Normandie University, 14000 Caen, France;5. USR CNRS 3413 SANPSY Sommeil, Addiction et NeuroPSYchiatrie, 33000 Bordeaux, France;6. Université Bordeaux, CHU de Bordeaux, 33000 Bordeaux, France |
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| Abstract: | Existing driver models mainly account for drivers’ responses to visual cues in manually controlled vehicles. The present study is one of the few attempts to model drivers’ responses to auditory cues in automated vehicles. It developed a mathematical model to quantify the effects of characteristics of auditory cues on drivers’ response to takeover requests in automated vehicles. The current study enhanced queuing network-model human processor (QN-MHP) by modeling the effects of different auditory warnings, including speech, spearcon, and earcon. Different levels of intuitiveness and urgency of each sound were used to estimate the psychological parameters, such as perceived trust and urgency. The model predictions of takeover time were validated via an experimental study using driving simulation with resultant R squares of 0.925 and root-mean-square-error of 73 ms. The developed mathematical model can contribute to modeling the effects of auditory cues and providing design guidelines for standard takeover request warnings for automated vehicles. |
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| Keywords: | QN-MHP Human performance modeling Takeover request Auditory warning Speech Non-speech Spearcon Driver model driver performance |
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