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An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios
For highly autonomous vehicles, human does not need to operate continuously vehicles. The brain-computer interface system in autonomous vehicles will...
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Driving risk cognition of passengers in highly automated driving based on the prefrontal cortex activity via fNIRS
For high-level automated vehicles, the human being acts as the passenger instead of the driver and does not need to operate vehicles, it makes the...
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A multimodal physiological dataset for driving behaviour analysis
Physiological signal monitoring and driver behavior analysis have gained increasing attention in both fundamental research and applied research. This...
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Turbulence suppression by cardiac-cycle-inspired driving of pipe flow
Flows through pipes and channels are, in practice, almost always turbulent, and the multiscale eddying motion is responsible for a major part of the...
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Map** urban mobility using vehicle telematics to understand driving behaviour
Telematics data, primarily collected from on-board vehicle devices (OBDs), has been utilised in this study to generate a thorough understanding of...
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A multimodal driver monitoring benchmark dataset for driver modeling in assisted driving automation
In driver monitoring various data types are collected from drivers and used for interpreting, modeling, and predicting driver behavior, and designing...
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Effect of driving characteristics and ambient temperature on the particle emissions during engine restart of spark ignition hybrid electric vehicle
In this study, we analyzed particle emission characteristics in the engine restart (ER) phase of a hybrid electric vehicle (HEV) based on driving...
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Study on evaluation method for driving fragment ability of explosives
The present study proposes an evaluation method for the driving fragment ability of explosives, which aims to provide theoretical and technical...
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Research on shock wave driving technology of methane explosion
In order to improve the driving ability of the explosion wave simulation equipment, reduce the erosion effect of condensed explosives on the...
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Mental workload accumulation effect of mobile phone distraction in L2 autopilot mode
As automated vehicles become more common, there is a need for precise measurement and definition of when and in what ways a driver can use a mobile...
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Construction and optimization of representative actual driving cycles based on the improved autoencoder
In this study, much work has been performed to accurately and efficiently develop representative actual driving cycles. Electric vehicle road tests...
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Blink-related EEG activity measures cognitive load during proactive and reactive driving
Assessing drivers’ cognitive load is crucial for driving safety in challenging situations. This research employed the occurrence of drivers’ natural...
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Driving forces of digital transformation in chinese enterprises based on machine learning
With advanced science and digital technology, digital transformation has become an important way to promote the sustainable development of...
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Tire mode shape categorization using Zernike annular moment and machine learning classification
This research proposes a framework for categorizing the radial tire mode shapes using machine learning (ML) based classification and feature...
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Vehicle-to-vehicle cooperative driving model considering end-to-end delay of communication network
To explore the mechanism of the end-to-end transmission delay of the communication network on the collaborative driving process for traffic flow in...
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Thermodynamic driving forces in contact electrification between polymeric materials
Contact electrification, or contact charging, refers to the process of static charge accumulation after rubbing, or even simple touching, of two...
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Optimal charge scheduling and on-board control of an urban electrified BRT fleet considering synthetic representative driving cycles
This paper presents a comprehensive approach for optimal charge scheduling and on-board vehicular control of electrified fleets based on synthetic...
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Driving chemical reactions with polariton condensates
When molecular transitions strongly couple to photon modes, they form hybrid light-matter modes called polaritons. Collective vibrational strong...
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A dynamic knowledge graph approach to distributed self-driving laboratories
The ability to integrate resources and share knowledge across organisations empowers scientists to expedite the scientific discovery process. This is...
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Parametrically driving a quantum oscillator into exceptionality
The mathematical objects employed in physical theories do not always behave well. Einstein’s theory of space and time allows for spacetime...
