Predictive modeling of human operators using parametric and neuro-fuzzy models by means of computer-based identification experiment

Driving a car and piloting an airplane are the most common examples for manual control of complicated processes. Human operators are known to be nonlinear, adaptive, time varying and intelligent controllers. In some cases, the human operator may or may not be well trained or an expert, showing different dynamics from operator to operator as in driving example. Therefore, it is very difficult to obtain mathematical models of human operators in a human-in-the-loop-manual control tasks. The goal of this research is to find a simple dynamic model for the prediction of the human operator actions in a manual control system. A computer-based experiment has been designed using the system identification theory to collect data from human operators. The autoregressive with exogenous inputs (ARX), as a parametric model and the adaptive-network-based fuzzy inference system (ANFIS), as an intelligent modeling approach that has the advantages of both neural networks and fuzzy logic, have been investigated and compared for simple and fast implementation to predict the response of human operators. ANFIS, having only 32 rules, provided much better prediction results than ARX model.     

The effect of stimulus modality on signal detection: implications for assessing the safety of in-vehicle technology

OBJECTIVE: This study examined the effect of two in-vehicle information systems (IVIS) on signal detection in the visual, auditory, and tactile modalities; established whether the detrimental effects of an IVIS on driving could be quantified by these detection tasks; and examined the effect of stimulus modality on signal detection. BACKGROUND: The peripheral detection task has been used widely for assessing the effects of an IVIS on driving. However, performance on this task relies on drivers' ability to see a series of LEDs, which can be problematic in field tests (e.g., on sunny days). METHOD: Participants responded to one of three detection tasks during a simulated driving experiment. The effect of IVIS interaction on these detection tasks was also measured. Reduced performance in the detection tasks was assumed to indicate a decline in drivers' ability to handle sudden events in the driving task. RESULTS: Response time to all detection tasks increased by around 200 ms when drivers performed the IVIS tasks, as compared with baseline driving. Analyses of variance and comparison of effect sizes showed the effects of these two IVISs to be the same across the three detection tasks. CONCLUSION: These detection tasks are useful for quantifying the safety of an IVIS during driving. The absence of a difference in signal detection by modality suggests that performance on these tasks relies on general attentional resources and is not modality specific. APPLICATION: The signal detection tasks employed here should be further investigated for their suitability in assessing the safety of in-vehicle systems.     

Effects of interface layout on the usability of In-Vehicle Information Systems and driving safety

This study investigated the impact of two In-Vehicle Information Systems (IVISs) on both usability and driving safety. We simulated vehicle checkerboard and hierarchical IVIS interface layouts and examined their usability based on task completion time, error rate, NASA-TLX, and System Usability Scale (SUS). Our driving safety measures included mean glance time, mean number of glances, blink frequency, and heart rate while real driving. The driving performances of 24 participants were recorded and assessed in real driving tasks of four driving speeds (0, 30, 60, and 80 km/h). Our results show that task completion time, SUS, and mean number of glances were significantly different with the two layouts. Moreover, we observed that the two layouts varied in their impacts on usability and driving safety at the different speeds. The hierarchical layout was more efficient at the lower speeds of 0 and 30 km/h, while the checkerboard layout outperformed at the higher speeds of 60 and 80 km/h. This study offers empirical evidence for IVIS interface design.     

Divided attention in experienced young and older drivers: lane tracking and visual analysis in a dynamic driving simulator.

A simulated driving task that required the simultaneous execution of two continuous visual tasks was administered to 12 healthy young (mean age 26.1 years) and 12 healthy older (mean age 64.4 years) experienced and currently active drivers. The first task was a compensatory lane-tracking task involving a three-dimensional road display. The second task was a timed, self-paced visual analysis task involving either a vocal or manual binary response to dot patterns projected within the road display. Using adaptive tasks, single-task difficulty was individually adjusted for each subject. To control for individual differences in attention allocation strategy, the dual task was performed according to three different sets of instructions based on the relative importance of each task. Compared with young adults, older adults showed a significantly decreased ability to divide attention. This effect was apparent in lane tracking and in the accuracy of visual analysis. The impairment of divided attention was less pronounced in the vocal condition than in the manual one. This suggests that difficulty in integrating responses may be an important determinant of poor dual-task performance in old age.     

The contractor time–cost–credit trade‐off problem: integer programming model,heuristic solution,and business insights

Contractors in the construction sector face several trade‐offs between time and cost. The time–cost trade‐off (TCT) is one of these trade‐offs where contractors can reduce a project completion time by assigning more resources to activities, which means spending more money, to shorten the execution times of project activities. On the other hand, contractors who finance their projects through credit lines from banks such that if they reach their credit limits, then the start times of some project activities can be delayed until cash is available again, which might lead to an increase in the project execution time; thus, contractors need to consider the time–credit trade‐off. In this work, we simultaneously consider these two trade‐offs that affect the project completion time and use mixed integer linear programming (MILP) to model the contractor time–cost–credit trade‐off (TCCT) problem. The MILP model minimizes the project execution time given the contractor's budgetary and financial constraints. In addition to the MILP model, we also develop a heuristic solution algorithm to solve the problem. Through a set of benchmark instances, we study the effectiveness of the heuristic algorithm and the computation time of the exact model. It is found that a good upper bound for the MILP results in less computation time. We also study some practical aspects of the problem where we highlight the importance of expediting contractor payments in addition to selecting a financially stable contractor. Finally, we use our MILP model to help a contractor bid for a project.     

Task analysis for computer-aided design (CAD) at a keystroke level

The purpose of this research was to develop a new model to describe and predict a computerized task. AutoCAD was utilized as the experimental tool to collect operating procedure and time data at a keystroke level for a computer aided design (CAD) task. Six undergraduate students participated in the experiment. They were required to complete one simple and one complex engineering drawing. A model which characterized the task performance by software commands and predicted task execution time using keystroke-level model operators was proposed and applied to the analysis of the dialogue data. This task parameter model adopted software commands, e.g. LINE, OFFSET in AutoCAD, to describe the function of a task unit and used up to five parameters to indicate the number of keystrokes, chosen function for a command and ways of starting and ending a command. Each task unit in the task parameter model can be replaced by a number of primitive operators as in the keystroke level model to predict the task execution time. The observed task execution times of all task units were found to be highly correlated with the task execution times predicted by the keystroke level model. Therefore, the task parameter model was proved to be a usable analytical tool for evaluating the human-computer interface (HCI).     

Robust static allocation of resources for independent tasks under makespan and dollar cost constraints

Heterogeneous computing (HC) systems composed of interconnected machines with varied computational capabilities often operate in environments where there may be inaccuracies in the estimation of task execution times. Makespan (defined as the completion time for an entire set of tasks) is often the performance feature that needs to be optimized in such systems. Resource allocation is typically performed based on estimates of the computation time of each task on each class of machines. Hence, it is important that makespan be robust against errors in computation time estimates. In this research, the problem of finding a static mapping of tasks to maximize the robustness of makespan against the errors in task execution time estimates given an overall makespan constraint is studied. Two variations of this basic problem are considered: (1) where there is a given, fixed set of machines, (2) where an HC system is to be constructed from a set of machines within a dollar cost constraint. Six heuristic techniques for each of these variations of the problem are presented and evaluated.     

Adaptive checkpointing strategy to tolerate faults in economy based grid

In this paper, we develop a fault tolerant job scheduling strategy in order to tolerate faults gracefully in an economy based grid environment. We propose a novel adaptive task checkpointing based fault tolerant job scheduling strategy for an economy based grid. The proposed strategy maintains a fault index of grid resources. It dynamically updates the fault index based on successful or unsuccessful completion of an assigned task. Whenever a grid resource broker has tasks to schedule on grid resources, it makes use of the fault index from the fault tolerant schedule manager in addition to using a time optimization heuristic. While scheduling a grid job on a grid resource, the resource broker uses fault index to apply different intensity of task checkpointing (inserting checkpoints in a task at different intervals). To simulate and evaluate the performance of the proposed strategy, this paper enhances the GridSim Toolkit-4.0 to exhibit fault tolerance related behavior. We also compare “checkpointing fault tolerant job scheduling strategy” with the well-known time optimization heuristic in an economy based grid environment. From the measured results, we conclude that even in the presence of faults, the proposed strategy effectively schedules grid jobs tolerating faults gracefully and executes more jobs successfully within the specified deadline and allotted budget. It also improves the overall execution time and minimizes the execution cost of grid jobs.     

Modelling the hare and the tortoise: predicting the range of in-vehicle task times using critical path analysis

Analytic models can enable predictions about important aspects of the usability of in-vehicle information systems (IVIS) to be made at an early stage of the product development process. Task times provide a quantitative measure of user performance and are therefore important in the evaluation of IVIS usability. In this study, critical path analysis (CPA) was used to model IVIS task times in a stationary vehicle, and the technique was extended to produce predictions for slowperson and fastperson performance, as well as average user (middleperson) performance. The CPA-predicted task times were compared to task times recorded in an empirical simulator study of IVIS interaction, and the predicted times were, on average, within acceptable precision limits. This work forms the foundation for extension of the CPA model to predict IVIS task times in a moving vehicle, to reflect the demands of the dual-task driving scenario.

Practitioner Summary: The CPA method was extended for the prediction of slowperson and fastperson IVIS task times. Comparison of the model predictions with empirical data demonstrated acceptable precision. The CPA model can be used in early IVIS evaluation; however, there is a need to extend it to represent the dual-task driving scenario.     

The validity of driving simulation for assessing differences between in-vehicle informational interfaces: A comparison with field testing

Data from on-road and simulation studies were compared to assess the validity of measures generated in the simulator. In the on-road study, driver interaction with three manual address entry methods (keypad, touch screen and rotational controller) was assessed in an instrumented vehicle to evaluate relative usability and safety implications. A separate group of participants drove a similar protocol in a medium fidelity, fixed-base driving simulator to assess the extent to which simulator measures mirrored those obtained in the field. Visual attention and task measures mapped very closely between the two environments. In general, however, driving performance measures did not differentiate among devices at the level of demand employed in this study. The findings obtained for visual attention and task engagement suggest that medium fidelity simulation provides a safe and effective means to evaluate the effects of in-vehicle information systems (IVIS) designs on these categories of driver behaviour.

Statement of Relevance: Realistic evaluation of the user interface of IVIS has significant implications for both user acceptance and safety. This study addresses the validity of driving simulation for accurately modelling differences between interface methodologies by comparing results from the field with those from a medium fidelity, fixed-base simulator.     

A Mathematical Task Dispatching Model in Wireless Sensor Actor Networks

In this paper, we propose a mathematical task dispatching model to reduce the total tasks completion time, i.e. make-span, in Wireless Sensor Actor Networks (WSANs). The proposed approach minimizes the completion time of tasks that have been allocated to actors but have not yet been dispatched to actors for execution in the networks. We calculate the best rate of dispatching of tasks by the network sink to allocated actors through a steady state analysis of our proposed model to solve equations and inequalities. It is shown that this dispatching rate improves the network lifetime too. Experimental results with a prototyped simulation of the proposed approach show shorter make-span and longer network lifetime compared to when one of the three famous task allocation algorithms, namely, the min-min, opportunistic load balancing (OLB), and stochastic allocation algorithms, is used.     

基于效益博弈的云计算资源动态可协调分配策略研究

在对用户的任务进行计算资源分配时,为了有效提高计算资源的利用效率,减少任务执行所需要的成本,提出了一种基于效益博弈的云计算资源动态可协调分配机制。该机制采用时间矩阵和费用矩阵作为任务效益的衡量指标,提出效益博弈模型,通过该模型的效益计算方程来得到最好的资源分配策略。为了使得计算资源能够合理地按需进行分配,提出了动态可协调分配机制,在合理地分配资源,满足所有任务正常执行时所需资源的同时,最大化任务的执行效益。实验仿真及对比结果表明,在任务完成时间、任务执行的平均成本、任务完成成功率上,本文算法都取得了较好的效果。     

Modeling and Analysis of Workflows Using Petri Nets

A workflow system, in its general form, is basically a heterogeneous and distributed information system where the tasks are performed using autonomous systems. Resources, such as databases, labor, etc. are typically required to process these tasks. Prerequisite to the execution of a task is a set of constraints that reflect the applicable business rules and user requirements.In this paper we present a Petri Net (PN) based framework that (1) facilitates specification of workflow applications, (2) serves as a powerful tool for modeling the system under study at a conceptual level, (3) allows for a smooth transition from the conceptual level to a testbed implementation and (4) enables the analysis, simulation and validation of the system under study before proceeding to implementation. Specifically, we consider three categories of task dependencies: control flow, value and external (temporal).We identify several structural properties of PN and demonstrate their use for conducting the following type of analyses: (1) identify inconsistent dependency specifications among tasks; (2) test for workflow safety, i.e. test whether the workflow terminates in an acceptable state; (3) for a given starting time, test whether it is feasible to execute a workflow with the specified temporal constraints. We also provide an implementation for conducting the above analyses.     

云中多媒体应用中基于混合DAG的最优任务调度研究

云计算的平台优势使得它在多媒体应用中得到广泛使用。由于多媒体服务的多样性和异构性,如何将多媒体任务有效地调度至虚拟机进行处理成为当前多媒体应用的研究重点。对此,研究了云中多媒体最优任务调度问题,首先引入有向无环图来模拟任务中的优先级及任务之间的依赖性,分别对串行、并行、混合结构任务调度模型进行任务调度研究,根据有限资源成本将关键路径中任务节点融合,提出一种实用的启发式近似最优调度方法。实验结果表明,所提调度方法能够以最短的执行时间在有限的资源成本下完成最优的任务分配。     

Approximate resolution of asynchronous conflicts among sequential collaborations in dynamic virtual environments

Asynchronous collaboration for a networked virtual environment (NVE) has emerged as a promising area in collaborative computer‐aided design applications. The concept of asynchronous collaboration is a sequential collaboration of temporal processes in an NVE where the participants are not required to be present at the time of the collaboration. Conflicts in asynchronous collaboration occur because the preceding task of a participant can influence the output of the ensuing task of another participant. The conflicted tasks must be modified manually. However, it requires considerable time and effort to resolve conflicts in a sequential collaboration. In this paper, we present an asynchronous collaborative framework that converts the conflict states of the shared objects into approximately resolved states. We develop a novel approximate resolution algorithm using a task‐based modeling mechanism to resolve the asynchronous conflicts with their corresponding tasks. Moreover, we propose a visual relation editor for convenient management. The participants can set flexible relations among shared objects using the proposed visual editor. The proposed approximate resolution approach can significantly reduce the average resolution time and the number of required manual task resolutions in a virtual environment compared to a manual resolution approach. Copyright © 2015 John Wiley & Sons, Ltd.     

The impact of drowsiness on in-vehicle human-machine interaction with head-up and head-down displays

Various studies show that drowsiness reduces driver alertness and can significantly affect driver performance. In this paper, we investigate the effect of drowsiness on the interaction with the in-vehicle infotainment system (IVIS) while driving. The motivation was to investigate whether a specific type of user interface can provide better performance and lower distraction when the driver is drowsy. The users were asked to navigate a vehicle in a driving simulator and simultaneously perform a set of tasks of varying complexity first when they were rested and alert and then when they were drowsy, after 7 h without sleep. A hierarchical, list-based menu was presented using a stereoscopic head-up display (HUD) and a head-down display (HDD). Based on the results, no general and statistically significant connection was found between drowsiness and driving performance. Surprisingly, the secondary task performance was even better when participants were drowsy, which was evident from the faster task completion times. This could be attributed to extra efforts invested in executing tasks as a result of the participants being aware of their drowsiness. However, when comparing the participants’ performance using HUD and HDD displays, the results showed that using HUD introduces less mental fatigue than using HDD but only in rested and alert condition. No significant difference between the displays was found in the drowsy state.     

面向可信嵌入式系统的随机实时任务能耗优化

针对可信嵌入式系统应用中将任务的最坏情况下的执行时间(WCET)作为任务的实际执行时间,导致系统资源的极大浪费的问题,提出了一种基于随机任务概率模型的方法。首先,考虑任务执行时间具有特定概率分布,并且任务具有不错过其死限的概率(NDVP)需求,同时考虑了动态电压和频率调整(DVFS)对系统可靠性的影响,利用该技术降低能耗。然后,基于动态规划算法,提出了一种具有多项式运行时间的优化算法,并进一步设计了状态剔除规则降低算法运行开销。仿真表明,所提算法与最坏执行时间模型下的最优算法相比,系统能耗降低了30%以上。实验结果表明,考虑任务的随机执行时间能在保证系统可靠性的同时大大节约系统资源。     

一种基于能耗优化的云计算系统任务调度方法

服务器执行任务产生的能耗是云计算系统动态能耗的重要组成部分。为降低云计算系统任务执行的总能耗,提出了一种基于能耗优化的最早完成时间任务调度方法,建立了服务器动态功率计算模型,基于动态功率的服务器执行能耗模型,以及云计算系统的能耗优化模型。调度策略根据任务的截止时间要求和在不同服务器上的执行能耗,选择不同的调度算法,以获得最小任务执行总能耗。实验结果证明,提出的任务调度方法,能够较好地满足任务截止时间的要求,降低云计算系统任务执行的总能耗。     

计算网格中基于时间均衡的并行粗粒度任务调度算法

考虑网格资源异构、自治、动态等特性,讨论本地用户具有强占优先权情况下的任务调度问题,提出了TBBS(Time-Balancing Based Scheduling Algorithm)算法.建立调度优化模型,以期望完成时间最小为目标选择执行任务的最佳资源组合.以时间均衡策略将任务分解并调度到资源上执行,减少了子任务同步时因等待而产生的延时,获得较好的并行计算性能.采用重复调度策略,适应计算网格中资源的特性.