ENABLING IMMERSIVE TECHNOLOGIES OF VIRTUAL/AUGMENTED/MIXED REALITY (VAMR) AND ELECTROENCEPHALOGRAPHY (EEG) FOR ENHANCED INTERACTION WITH AUTONOMOUS VEHICLES
Publish Year: 1397
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ENAUI01_030
تاریخ نمایه سازی: 21 خرداد 1398
Abstract:
Emerging immersive technologies comprising Virtual, Augmented and Mixed Reality (VAMR) and Electroencephalography (EEG) environments have currently developed platforms for creating revolutionary and non-invasive Brain Robot interaction paradigms. The proliferation of these technologies in near future will ensue a new era of novel human interfaces juxtaposing VAMR platforms with neuro-monitoring and neuro-feedback genre in multifarious fields of healthcare, business, education, gaming and robotics. The burgeoning rise of autonomy in the vehicles and expected introduction of self-driving ones will underpin the interesting use of such technologies creating a brain to vehicle connectivity, digitalization, efficiency, improved situational awareness, portable environment for riders and provision of safe testing grounds in real-time conditions. Despite the increased industrial interest, less attention has been paid by the academia in the use of such immersive technologies in the testing and operation of autonomous vehicles. This exploratory research study is an attempt to venture into these enabling immersive technology applications and explore their role in a wider industry with special focus to driverless vehicles. In this study, a research attempt has been made to glean into these immersive technologies and emphasize their specific academic relevance besides generating a thought process with an appropriate synthesis of recent and systematic literature review of immersive technology research in diverse settings.
Keywords:
Virtual , Augmented and Mixed Reality (VAMR) , Electroencephalography (EEG) , Autonomous Vehicles (AV) , Human Computer Interaction (HCI) , Brain – computer interfaces (BCIs) , Brain Robotic Interface (BRI)
Authors
Ali Ghaffarianhoseini
Department of Built Environment Engineering, School of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, New Zealand
Attiq Ur Rehman
Department of Built Environment Engineering, School of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, New Zealand
Tongrui Zhang
Department of Built Environment Engineering, School of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, New Zealand
Dat Tien Doan
Department of Built Environment Engineering, School of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, New Zealand