Real-time Human Workload Estimation and Its Application in Adaptive Haptic Shared Control

Automated vehicles (AVs) are promising to have the potential to reduce driving-related injuries and deaths. However, autonomous driving technology is currently limited in its scope and reliability, giving rise to the semi-autonomous driving model, where the autonomy and the human share the control of the vehicle. Workload, despite being an important human factor, has not yet been considered when designing adaptive shared control. Recently, researchers have started to apply machine learning techniques to classify mental workload into different levels. However, most of these studies have adopted either a single-model-single-feature approach or a single-model-all-features approach. However different machine learning models are suitable for different features, how to leverage different models for different features is critical. To address these shortcomings and research gaps, the goals of this dissertation were to (1) examine whether and to what extent haptic shared control performance can be improved by incorporating operators' workload; (2) develop a computational model for workload estimation, and the model should be able to leverage different machine learning models that work best for different features; and (3) investigate the generalizability of the workload estimation model. To address these research goals, this dissertation was composed of four research phases with two pilot studies and four human subject experiments. (1) Collaborating with Yifan Weng, Dr. Tulga Ersal, and Prof. Jeffrey Stein from the Department of Mechanical Engineering at the University of Michigan, we developed a teleoperated dual-task shared control simulation platform where the human shared control of a ground vehicle with autonomy while performing a surveillance task simultaneously. In addition, we developed a real-time eye-tracking system based on Tobii Pro Glasses 2 to measure the human gaze points in a world frame and pupil sizes. (2) We proposed a workload-adaptive haptic shared control scheme together with our collaborators. We conducted two human subject experiments during this phase. The results indicated that the proposed workload-adaptive haptic shared control scheme can reduce human workload, increase human trust in the system, increase driving performance, and reduce human effort without sacrificing surveillance task performance. (3) We proposed a Bayesian inference model for workload estimation that can leverage the different machine learning models that work best for different features. Specifically, we used support-vector machines (SVMs) for pupil size change, the Hidden Markov Model (HMM) for gaze trajectory, SVMs for fixation feature, and Gaussian Mixture Models (GMMs) for fixation trajectory. The empirical results indicated that our proposed model achieved a 0.82 F1 score for workload imposed by varying surveillance task urgency. (4) We investigated the generalizability of our proposed Bayesian inference model for workload estimation by conducting two human subject experiments with 24 participants and using different factors to impose human workload, i.e., obstacle headway and driving speed. The results indicated that our proposed model achieved a 0.68 F1 score for the workload imposed by obstacle avoidance and the personalized version of our proposed model can distinguish the workload imposed by different driving speeds under high surveillance task urgency.PHDRoboticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169623/1/ruikunl_1.pd

Research and Application of Capacitive Power Transfer System: A Review

Capacitive power transfer (CPT) uses an electric field as the transfer medium to achieve wireless power transfer (WPT). Benefitting from the low eddy current loss, simple system structure and strong plasticity of the coupling coupler, the CPT system has recently gained much attention. The CPT system has significantly improved transfer power, system efficiency, and transfer distance due to continuous research and discussion worldwide. This review briefly presents the basic working principle of the CPT system and summarizes the theoretical research in four aspects, including coupling coupler and high-frequency power converter. Following this, the review focuses on research in six key directions, including system modelling and efficiency optimization. The application of CPT technology in five fields, including medical devices and transportation, is also discussed. This review introduces the progress of CPT research in recent years, hoping to serve as a reference for researchers, to promote the further research and application of the CPT system

Research and Application of Capacitive Power Transfer System: A Review

Capacitive power transfer (CPT) uses an electric field as the transfer medium to achieve wireless power transfer (WPT). Benefitting from the low eddy current loss, simple system structure and strong plasticity of the coupling coupler, the CPT system has recently gained much attention. The CPT system has significantly improved transfer power, system efficiency, and transfer distance due to continuous research and discussion worldwide. This review briefly presents the basic working principle of the CPT system and summarizes the theoretical research in four aspects, including coupling coupler and high-frequency power converter. Following this, the review focuses on research in six key directions, including system modelling and efficiency optimization. The application of CPT technology in five fields, including medical devices and transportation, is also discussed. This review introduces the progress of CPT research in recent years, hoping to serve as a reference for researchers, to promote the further research and application of the CPT system

Cost-Effective Edge Server Network Design in Mobile Edge Computing Environment

Mobile edge computing (MEC) deploys edge servers at the base station in the proximity of users to provide cloud computing-like computing and storage functionalities, which can achieve applications' low latency requirement at the network edge. The edge server network (ESN), constituted by edge servers in an area and the links between them, can host app vendors' services for serving nearby users. Many existing studies have demonstrated that a high ESN density allows for high service performance because edge servers can communicate and share resources with each other effectively over the ESN. However, in the real-world MEC environment, constructing a high-density ESN may incur high construction costs. The trade-off between construction cost and network density plays a vital role in the design of an ESN. Unfortunately, existing studies of MEC have commonly and simply assumed the densities of the ESNs in their experiments. In this paper, we make the first attempt to study the design of cost-effective ESNs with the aim to trade off between the network construction cost and the network density. ESND-O as an optimal approach is proposed based on integer programming to solve small-scale ESND problems. Another approximation approach named ESND-A is designed to solve large-scale ESND problems efficiently. We conduct extensive experiments to test the performance of ESND-O and ESND-A on a real-world dataset, and the experimental results demonstrate their effectiveness and efficiency against four representative approache

Cost-Effective Data Placement in Edge Storage Systems with Erasure Code

In this paper, we make the first attempt to investigate the use of erasure codes in cost-effective data storage at the edge. The focus is to find the optimal strategy for placing coded data blocks on the edge servers in an ESS, aiming to minimize the storage cost while serving all the users in the system. We first model this novel Erasure Coding based Edge Data Placement (EC-EDP) problem as a constrained optimization problem and prove that it is NP-hard. Then, we propose an optimal approach named EC-EDP-O based on integer programming. We also propose an approximation algorithm named EC-EDP-V for finding approximate solutions to large-scale EC-EDP problems efficiently. The results of experiments conducted on a widely-used real-world dataset demonstrate that EC-EDP-O and EC-EDP-V can save an average of 68.58% (and up to 81.16% in large-scale scenarios) storage cost compared with replica-based storage approaches

Optimal Load Determination of Capacitor–Inductor Compensated Capacitive Power Transfer System with Curved-Edge Shielding Layer

Due to the natural low permittivity in vacuum, the voltage stresses on compensation capacitors and inductances in the capacitive power transfer (CPT) system are very high, which brings challenges to the design of CPT systems in practical applications. This paper used a three-cell structure analysis method for the CPT system to determine the optimal load for achieving the maximum power transfer or maximum efficiency transfer, through considering the maximum withstand voltage of the capacitor or inductor. A shielding layer with edge bending is designed to reduce the range of dangerous areas markedly. The simulation and experimental results verified the above conclusion. The prototype of the CPT system with transfer 3.1 kW across a 13 cm air gap and DC-DC transfer efficiency of 91.4% is built

<i>Vaccinium</i> as Potential Therapy for Diabetes and Microvascular Complications

Diabetes mellitus is one of the most critical global health concerns, with a fast-growing prevalence. The incidence of diabetic vascular complications is also rapidly increasing, exacerbating the burden on individuals with diabetes and the consumption of public medical resources. Despite the overall improvements in the prevention, diagnosis, and treatment of diabetic microvascular complications in recent years, safe and effective alternative or adjunctive therapies are urgently needed. The mechanisms underlying diabetic vascular complications are complex, with hyperglycemia-induced oxidative stress and inflammation being the leading causes. Therefore, glycemic control, antioxidation, and anti-inflammation are considered the main targets for the treatment of diabetes and its vascular comorbidities. Vaccinium L. (Ericaceae) is a genus of plants enriched with polyphenolic compounds in their leaves and fruits. Vaccinium and its extracts have demonstrated good bioactivity in reducing blood glucose, oxidative stress, and inflammation, making them excellent candidates for the management of diabetes and diabetic vascular complications. Here, we review recent preclinical and clinical studies on the potential effect of Vaccinium on ameliorating diabetes and diabetic complications, particularly diabetic kidney disease and diabetic retinopathy