Smartphones as an integrated platform for monitoring driver behaviour: The role of sensor fusion and connectivity |
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| Institution: | 1. Faculty of Engineering, Environment and Computing, Coventry University, Priory Street, Coventry CV1 5FB, United Kingdom;2. Solid Earth Physics Institute, Faculty of Physics, National and Kapodistrian University of Athens, Panepistimiopolis, Zografos 157 84, Athens, Greece;1. Department of Computer Science, Amirkabir University of Technology, N. 424, Hafez Avenue, Tehran 15875-4413, Iran;2. Intelligent Transportation Systems Research Institute, Amirkabir University of Technology, Tehran, Iran;1. Centre for Accident Research Road Safety, Queensland, Australia;2. Computer Human Interaction Group, Queensland University of Technology, Australia;1. Aeronautical Systems, Air Transport and Airports Department, Universidad Politécnica de Madrid, Madrid, Spain;2. Centre for Aeronautics, School of Aerospace, Transport and Manufacturing. Cranfield University, Cranfield, United Kingdom;3. CRIDA A.I.E., Madrid, Spain |
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| Abstract: | Nowadays, more than half of the world’s web traffic comes from mobile phones, and by 2020 approximately 70 percent of the world’s population will be using smartphones. The unprecedented market penetration of smartphones combined with the connectivity and embedded sensing capability of smartphones is an enabler for the large-scale deployment of Intelligent Transportation Systems (ITS). On the downside, smartphones have inherent limitations such as relatively limited energy capacity, processing power, and accuracy. These shortcomings may potentially limit their role as an integrated platform for monitoring driver behaviour in the context of ITS. This study examines this hypothesis by reviewing recent scientific contributions. The Cybernetics theoretical framework was employed to allow a systematic comparison. First, only a few studies consider the smartphone as an integrated platform. Second, a lack of consistency between the approaches and metrics used in the literature is noted. Last but not least, areas such as fusion of heterogeneous information sources, Deep Learning and sparse crowd-sensing are identified as relatively unexplored, and future research in these directions is suggested. |
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| Keywords: | Smartphones Driver behaviour Sensor fusion Connectivity Cybernetics Crowd-sensing |
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