Human resource behaviour simulation in business processes

The structure and dynamics of a modern business environment are very hard to model using traditional methods. Such complexity raises challenges to effective business analysis and improvement. The importance of applying business process simulation to analyze and improve business activities has been widely recognized. However, one remaining challenge is the development of approaches to human resource behavior simulation. To address this problem, we describe a novel simulation approach where intelligent agents are used to simulate human resources by performing allocated work from a workflow management system. The behavior of the intelligent agents is driven a by state transition mechanism called a Hierarchical Task Network (HTN). We demonstrate and validate our simulator via a medical treatment process case study. Analysis of the simulation results shows that the behavior driven by the HTN is consistent with design of the workflow model. We believe these preliminary results support the development of more sophisticated agent-based human resource simulation systems.

QoC Elastic Scheduling for Real-Time Control Systems

The elastic task model, a significant development in scheduling of real-time control tasks, provides a mechanism for flexible workload management in uncertain environments. It tells how to adjust the control periods to fulfill the workload constraints. However, it is not directly linked to the quality-of-control (QoC) management, the ultimate goal of a control system. As a result, it does not tell how to make the best use of the system resources to maximize the QoC improvement. To fill in this gap, a new feedback scheduling framework, which we refer to as QoC elastic scheduling, is developed in this paper for real-time process control systems. It addresses the QoC directly through embedding both the QoC management and workload adaptation into a constrained optimization problem. The resulting solution for period adjustment is in a closed-form expressed in QoC measurements, enabling closed-loop feedback of the QoC to the task scheduler. Whenever the QoC elastic scheduler is activated, it improves the QoC the most while still meeting the system constraints. Examples are given to demonstrate the effectiveness of the QoC elastic scheduling.

An examination of monotony and hypovigilance, independent of fatigue : relevance to road safety

Driving is a vigilance task, requiring sustained attention to maintain performance and avoid crashes. Hypovigilance (i.e., marked reduction in vigilance) while driving manifests as poor driving performance and is commonly attributed to fatigue (Dinges, 1995). However, poor driving performance has been found to be more frequent when driving in monotonous road environments, suggesting that monotony plays a role in generating hypovigilance (Thiffault & Bergeron, 2003b). Research to date has tended to conceptualise monotony as a uni-dimensional task characteristic, typically used over a prolonged period of time to facilitate other factors under investigation, most notably fatigue. However, more often than not, more than one exogenous factor relating to the task or operating environment is manipulated to vary or generate monotony (Mascord & Heath, 1992). Here we aimed to explore whether monotony is a multi-dimensional construct that is determined by characteristics of both the task proper and the task environment. The general assumption that monotony is a task characteristic used solely to elicit hypovigilance or poor performance related to fatigue appears to have led to there being little rigorous investigation into the exact nature of the relationship. While the two concepts are undoubtedly linked, the independent effect of monotony on hypovigilance remains largely ignored. Notwithstanding, there is evidence that monotony effects can emerge very early in vigilance tasks and are not necessarily accompanied by fatigue (see Meuter, Rakotonirainy, Johns, & Wagner, 2005). This phenomenon raises a largely untested, empirical question explored in two studies: Can hypovigilance emerge as a consequence of task and/or environmental monotony, independent of time on task and fatigue? In Study 1, using a short computerised vigilance task requiring responses to be withheld to infrequent targets, we explored the differential impacts of stimuli and task demand manipulations on the development of a monotonous context and the associated effects on vigilance performance (as indexed by respone errors and response times), independent of fatigue and time on task. The role of individual differences (sensation seeking, extroversion and cognitive failures) in moderating monotony effects was also considered. The results indicate that monotony affects sustained attention, with hypovigilance and associated performance worse in monotonous than in non-monotonous contexts. Critically, performance decrements emerged early in the task (within 4.3 minutes) and remained consistent over the course of the experiment (21.5 minutes), suggesting that monotony effects can operate independent of time on task and fatigue. A combination of low task demands and low stimulus variability form a monotonous context characterised by hypovigilance and poor task performance. Variations to task demand and stimulus variability were also found to independently affect performance, suggesting that monotony is a multi-dimensional construct relating to both task monotony (associated with the task itself) and environmental monotony (related to characteristics of the stimulus). Consequently, it can be concluded that monotony is multi-dimensional and is characterised by low variability in stimuli and/or task demands. The proposition that individual differences emerge under conditions of varying monotony with high sensation seekers and/or extroverts performing worse in monotonous contexts was only partially supported. Using a driving simulator, the findings of Study 1 were extended to a driving context to identify the behavioural and psychophysiological indices of monotony-related hypovigilance associated with variations to road design and road side scenery (Study 2). Supporting the proposition that monotony is a multi-dimensional construct, road design variability emerged as a key moderating characteristic of environmental monotony, resulting in poor driving performance indexed by decrements in steering wheel measures (mean lateral position). Sensation seeking also emerged as a moderating factor, where participants high in sensation seeking tendencies displayed worse driving behaviour in monotonous conditions. Importantly, impaired driving performance was observed within 8 minutes of commencing the driving task characterised by environmental monotony (low variability in road design) and was not accompanied by a decline in psychophysiological arousal. In addition, no subjective declines in alertness were reported. With fatigue effects associated with prolonged driving (van der Hulst, Meijman, & Rothengatter, 2001) and indexed by drowsiness, this pattern of results indicates that monotony can affect driver vigilance, independent of time on task and fatigue. Perceptual load theory (Lavie, 1995, 2005) and mindlessness theory (Robertson, Manly, Andrade, Baddley, & Yiend, 1997) provide useful theoretical frameworks for explaining and predicting monotony effects by positing that the low load (of task and/or stimuli) associated with a monotonous task results in spare attentional capacity which spills over involuntarily, resulting in the processing of task-irrelevant stimuli or task unrelated thoughts. That is, individuals – even when not fatigued - become easily distracted when performing a highly monotonous task, resulting in hypovigilance and impaired performance. The implications for road safety, including the likely effectiveness of fatigue countermeasures to mitigate monotony-related driver hypovigilance are discussed.

Evaluating effects of eco-driving at traffic intersections based on traffic micro-simulation

Eco-driving is an initiative driving behavior which aims to reduce fuel consumption and emissions from automobiles. Recently, it has attracted increasing interests and has been adopted by many drivers in Australia. Although many of the studies have revealed considerable benefits in terms of fuel consumption and emissions after utilising eco-driving, most of the literature investigated eco-driving effects on individual driver but not traffic flow. The driving behavior of eco-drivers will potentially affect other drivers and thereby affects the entire traffic flow. To comprehensively assess and understand how effectively eco-driving can perform, therefore, measurement on traffic flow is necessary. In this paper, we proposed and demonstrated an evaluation method based on a microscopic traffic simulator (Aimsun). We focus on one particular eco-driving style which involves moderate and smooth acceleration. We evaluated both traffic performance (travel time) and environmental performance (fuel consumption and CO2 emission) at traffic intersection level in a simple simulation model. The before-and-after comparisons indicated potentially negative impacts when using eco-driving, which highlighted the necessity to carefully evaluate and improve eco-driving before wide promotion and implementation.

Measuring driver responses at railway level crossings

Railway level crossings are amongst the most complex of road safety control systems, due to the conflicts between road vehicles and rail infrastructure, trains and train operations. Driver behaviour at railway crossings is the major collision factor. The main objective of the present paper was to evaluate the existing conventional warning devices in relation to driver behaviour. The common conventional warning devices in Australia are a stop sign (passive), flashing lights and a half boom-barrier with flashing lights (active). The data were collected using two approaches, namely: field video recordings at selected sites and a driving simulator in a laboratory. This paper describes and compares the driver response results from both the field survey and the driving simulator. The conclusion drawn is that different types of warning systems resulted in varying driver responses at crossings. The results showed that on average driver responses to passive crossings were poor when compared to active ones. The field results were consistent with the simulator results for the existing conventional warning devices and hence they may be used to calibrate the simulator for further evaluation of alternative warning systems.

Effects of climate change on the wash-off of volatile organic compounds from urban roads

The predicted changes in rainfall characteristics due to climate change could adversely affect stormwater quality in highly urbanised coastal areas throughout the world. This in turn will exert a significant influence on the discharge of pollutants to estuarine and marine waters. Hence, an in-depth analysis of the effects of such changes on the wash-off of volatile organic compounds (VOCs) from urban roads in the Gold Coast region in Australia was undertaken. The rainfall characteristics were simulated using a rainfall simulator. Principal Component Analysis (PCA) and Multicriteria Decision tools such as PROMETHEE and GAIA were employed to understand the VOC wash-off under climate change. It was found that low, low to moderate and high rain events due to climate change will affect the wash-off of toluene, ethylbenzene, meta-xylene, para-xylene and ortho-xylene from urban roads in Gold Coast. Total organic carbon (TOC) was identified as predominant carrier of toluene, meta-xylene and para-xylene in <1µm to 150µm fractions and for ethylbenzene in 150µm to >300µm fractions under such dominant rain events due to climate change. However, ortho-xylene did not show such affinity towards either TOC or TSS (total suspended solids) under the simulated climatic conditions.

Using cooperative vehicle systems to collect near collision incidents events : a simulation study

On the road, near collision events (also close calls or near-miss incidents) largely outnumber actual crashes, yet most of them can never be recorded by current traffic data collection technologies or crashes analysis tools. The analysis of near collisions data is an important step in the process of reducing the crash rate. There have been several studies that have investigated near collisions; to our knowledge, this is the first study that uses the functionalities provided by cooperative vehicles to collect near misses information. We use the VISSIM traffic simulator and a custom C++ engine to simulate cooperative vehicles and their ability to detect near collision events. Our results showed that, within a simple simulated environment, adequate information on near collision events can be collected using the functionalities of cooperative perception systems. The relationship between the ratio of detected events and the ratio of equipped vehicle was shown to closely follow a squared law, and the largest source of nondetection was packet loss instead of packet delays and GPS imprecision.

In search of the antecendents for risky driving at railway level crossings

This paper discusses human factors issues of low cost railway level crossings in Australia. Several issues are discussed in this paper including safety at passive level railway crossings, human factors considerations associated with unavailability of a warning device, and a conceptual model for how safety could be compromised at railway level crossings following prolonged or frequent unavailability. The research plans to quantify safety risk to motorists at level crossings using a Human Reliability Assessment (HRA) method, supported by data collected using an advanced driving simulator. This method aims to identify human error within tasks and task units identified as part of the task analysis process. It is anticipated that by modelling driver behaviour the current study will be able to quantify meaningful task variability including temporal parameters, between participants and within participants. The process of complex tasks such as driving through a level crossing is fundamentally context-bound. Therefore this study also aims to quantify those performance-shaping factors that contribute to vehicle train collisions by highlighting changes in the task units and driver physiology. Finally we will also consider a number of variables germane to ensuring external validity of our results. Without this inclusion, such an analysis could seriously underestimate the probabilistic risk assessment.

Adaptive cache aware multiprocessor scheduling framework

Computer resource allocation represents a significant challenge particularly for multiprocessor systems, which consist of shared computing resources to be allocated among co-runner processes and threads. While an efficient resource allocation would result in a highly efficient and stable overall multiprocessor system and individual thread performance, ineffective poor resource allocation causes significant performance bottlenecks even for the system with high computing resources. This thesis proposes a cache aware adaptive closed loop scheduling framework as an efficient resource allocation strategy for the highly dynamic resource management problem, which requires instant estimation of highly uncertain and unpredictable resource patterns. Many different approaches to this highly dynamic resource allocation problem have been developed but neither the dynamic nature nor the time-varying and uncertain characteristics of the resource allocation problem is well considered. These approaches facilitate either static and dynamic optimization methods or advanced scheduling algorithms such as the Proportional Fair (PFair) scheduling algorithm. Some of these approaches, which consider the dynamic nature of multiprocessor systems, apply only a basic closed loop system; hence, they fail to take the time-varying and uncertainty of the system into account. Therefore, further research into the multiprocessor resource allocation is required. Our closed loop cache aware adaptive scheduling framework takes the resource availability and the resource usage patterns into account by measuring time-varying factors such as cache miss counts, stalls and instruction counts. More specifically, the cache usage pattern of the thread is identified using QR recursive least square algorithm (RLS) and cache miss count time series statistics. For the identified cache resource dynamics, our closed loop cache aware adaptive scheduling framework enforces instruction fairness for the threads. Fairness in the context of our research project is defined as a resource allocation equity, which reduces corunner thread dependence in a shared resource environment. In this way, instruction count degradation due to shared cache resource conflicts is overcome. In this respect, our closed loop cache aware adaptive scheduling framework contributes to the research field in two major and three minor aspects. The two major contributions lead to the cache aware scheduling system. The first major contribution is the development of the execution fairness algorithm, which degrades the co-runner cache impact on the thread performance. The second contribution is the development of relevant mathematical models, such as thread execution pattern and cache access pattern models, which in fact formulate the execution fairness algorithm in terms of mathematical quantities. Following the development of the cache aware scheduling system, our adaptive self-tuning control framework is constructed to add an adaptive closed loop aspect to the cache aware scheduling system. This control framework in fact consists of two main components: the parameter estimator, and the controller design module. The first minor contribution is the development of the parameter estimators; the QR Recursive Least Square(RLS) algorithm is applied into our closed loop cache aware adaptive scheduling framework to estimate highly uncertain and time-varying cache resource patterns of threads. The second minor contribution is the designing of a controller design module; the algebraic controller design algorithm, Pole Placement, is utilized to design the relevant controller, which is able to provide desired timevarying control action. The adaptive self-tuning control framework and cache aware scheduling system in fact constitute our final framework, closed loop cache aware adaptive scheduling framework. The third minor contribution is to validate this cache aware adaptive closed loop scheduling framework efficiency in overwhelming the co-runner cache dependency. The timeseries statistical counters are developed for M-Sim Multi-Core Simulator; and the theoretical findings and mathematical formulations are applied as MATLAB m-file software codes. In this way, the overall framework is tested and experiment outcomes are analyzed. According to our experiment outcomes, it is concluded that our closed loop cache aware adaptive scheduling framework successfully drives co-runner cache dependent thread instruction count to co-runner independent instruction count with an error margin up to 25% in case cache is highly utilized. In addition, thread cache access pattern is also estimated with 75% accuracy.

A human factors investigation into the unavailability of active warnings at railway level crossings

This paper discusses human factors issues of low cost railway level crossings in Australia. Several issues are discussed in this paper including safety at passive level railway crossings, human factors considerations associated with unavailability of a warning device, and a conceptual model for how safety could be compromised at railway level crossings following prolonged or frequent unavailability. The research plans to quantify safety risk to motorists at level crossings using a Human Reliability Assessment (HRA) method, supported by data collected using an advanced driving simulator. This method aims to identify human error within tasks and task units identified as part of the task analysis process. It is anticipated that by modelling driver behaviour the current study will be able to quantify meaningful task variability including temporal parameters, between participants and within participants. The process of complex tasks such as driving through a level crossing is fundamentally context-bound. Therefore this study also aims to quantify those performance-shaping factors that contribute to vehicle train collisions by highlighting changes in the task units and driver physiology. Finally we will also consider a number of variables germane to ensuring external validity of our results. Without this inclusion, such an analysis could seriously underestimate risk.

Design and implementation of a virtual world training simulation of ICU first hour handover processes

Nursing training for an Intensive Care Unit (ICU) is a resource intensive process. High demands are made on staff, students and physical resources. Interactive, 3D computer simulations, known as virtual worlds, are increasingly being used to supplement training regimes in the health sciences; especially in areas such as complex hospital ward processes. Such worlds have been found to be very useful in maximising the utilisation of training resources. Our aim is to design and develop a novel virtual world application for teaching and training Intensive Care nurses in the approach and method for shift handover, to provide an independent, but rigorous approach to teaching these important skills. In this paper we present a virtual world simulator for students to practice key steps in handing over the 24/7 care requirements of intensive care patients during the commencing first hour of a shift. We describe the modelling process to provide a convincing interactive simulation of the handover steps involved. The virtual world provides a practice tool for students to test their analytical skills with scenarios previously provided by simple physical simulations, and live on the job training. Additional educational benefits include facilitation of remote learning, high flexibility in study hours and the automatic recording of a reviewable log from the session. To the best of our knowledge, we believe this is a novel and original application of virtual worlds to an ICU handover process. The major outcome of the work was a virtual world environment for training nurses in the shift handover process, designed and developed for use by postgraduate nurses in training.

Reducing aggression on our roads : testing a comprehensive model of aggressive driving

Background: Trauma resulting from traffic crashes poses a significant problem in highly motorised countries. Over a million people worldwide are killed annually and 50 million are critically injured as a result of traffic collisions. In Australia, road crashes cost an average of $17 billion annually in personal loss of income and quality of life, organisational losses in productivity and workplace quality, and health care costs. Driver aggression has been identified as a key factor contributing to crashes, and many motorists report experiencing mild forms of aggression (e.g., rude gestures, horn honking). However despite this concern, driver aggression has received relatively little attention in empirical research, and existing research has been hampered by a number of methodological and conceptual shortcomings. Specifically, there has been substantial disagreement regarding what constitutes aggressive driving and a failure to examine both the situational factors and the emotional and cognitive processes underlying driver aggression. To enhance current understanding of aggressive driving, a model of driver aggression that highlights the cognitive and emotional processes at play in aggressive driving incidents is proposed. Aims: The research aims to improve current understanding of the complex nature of driver aggression by testing and refining a model of aggressive driving that incorporates the person-related and situational factors and the cognitive and emotional appraisal processes fundamental to driver aggression. In doing so, the research will assist to provide a clear definition of what constitutes aggressive driving, assist to identify on-road incidents that trigger driver aggression, and identify the emotional and cognitive appraisal processes that underlie driver aggression. Methods: The research involves three studies. Firstly, to contextualise the model and explore the cognitive and emotional aspects of driver aggression, a diary-based study using self-reports of aggressive driving events will be conducted with a general population of drivers. This data will be supplemented by in-depth follow-up interviews with a sub-sample of participants. Secondly, to test generalisability of the model, a large sample of drivers will be asked to respond to video-based scenarios depicting driving contexts derived from incidents identified in Study 1 as inciting aggression. Finally, to further operationalise and test the model an advanced driving simulator will be used with sample of drivers. These drivers will be exposed to various driving scenarios that would be expected to trigger negative emotional responses. Results: Work on the project has commenced and progress on the first study will be reported.

A focus on risk compensation and its role in motor vehicle crashes

• What is risk compensation, and why is relevant to motor vehicle crashes? • Recent simulator work that revealed risk compensation • Current and future work on risk compensation

Considering weather in simulation traffic

The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.

Force controlled hexapod walking

In this paper we describe the dynamic simulation of an 18 degrees of freedom hexapod robot with the objective of developing control algorithms for smooth, efficient and robust walking in irregular terrain. This is to be achieved by using force sensors in addition to the conventional joint angle sensors as proprioceptors. The reaction forces on the feet of the robot provide the necessary information on the robots interaction with the terrain. As a first step we validate the simulator by implementing movement control by joint torques using PID controllers. As an unexpected by-product we find that it is simple to achieve robust walking behaviour on even terrain for a hexapod with the help of PID controllers and by specifying a trajectory of only a few joint configurations.