Development of a generic activities model of command and control

This paper reports on five different models of command and control. Four different models are reviewed: a process model, a contextual control model, a decision ladder model and a functional model. Further to this, command and control activities are analysed in three distinct domains: armed forces, emergency services and civilian services. From this analysis, taxonomies of command and control activities are developed that give rise to an activities model of command and control. This model will be used to guide further research into technological support of command and control activities

The ergonomics of command and control

Since its inception, just after the Second World War, ergonomics research has paid special attention to the issues surrounding human control of systems. Command and Control environments continue to represent a challenging domain for Ergonomics research. We take a broad view of Command and Control research, to include C2 (Command and Control), C3 (Command, Control and Communication), and C4 (Command, Control, Communication and Computers) as well as human supervisory control paradigms. This special issue of ERGONOMICS aims to present state-of-the-art research into models of team performance, evaluation of novel interaction technologies, case studies, methodologies and theoretical review papers. We are pleased to present papers that detail research on these topics in domains as diverse as the emergency services (e.g., police, fire, and ambulance), civilian applications (e.g., air traffic control, rail networks, and nuclear power) and military applications (e.g., land, sea and air) of command and control. While the domains of application are very diverse, many of the challenges they face share interesting similarities

Longitudinal Dynamic versus Kinematic Models for Car-Following Control Using Deep Reinforcement Learning

The majority of current studies on autonomous vehicle control via deep reinforcement learning (DRL) utilize point-mass kinematic models, neglecting vehicle dynamics which includes acceleration delay and acceleration command dynamics. The acceleration delay, which results from sensing and actuation delays, results in delayed execution of the control inputs. The acceleration command dynamics dictates that the actual vehicle acceleration does not rise up to the desired command acceleration instantaneously due to dynamics. In this work, we investigate the feasibility of applying DRL controllers trained using vehicle kinematic models to more realistic driving control with vehicle dynamics. We consider a particular longitudinal car-following control, i.e., Adaptive Cruise Control (ACC), problem solved via DRL using a point-mass kinematic model. When such a controller is applied to car following with vehicle dynamics, we observe significantly degraded car-following performance. Therefore, we redesign the DRL framework to accommodate the acceleration delay and acceleration command dynamics by adding the delayed control inputs and the actual vehicle acceleration to the reinforcement learning environment state, respectively. The training results show that the redesigned DRL controller results in near-optimal control performance of car following with vehicle dynamics considered when compared with dynamic programming solutions.Comment: Accepted to 2019 IEEE Intelligent Transportation Systems Conferenc

Regulatory Strategies

Over the years, there has been a shift from a wide command-and-control style of supervision whereby the regulator imposes detailed rules with which regulators supervise to one which consists of risk based regulatory strategies. ‘Enforced Self Regulation’, a regulatory strategy whereby negotiation takes places between the State and the individual firms, lies between the command-and-control style of supervision and meta risk regulation in that firms are still required to regulate but according to their own models. It differs from the traditional command-and-control style of bank supervision in that firms and not the regulator, are required to regulate. It is similar to meta-risk regulation in that the individual firm’s model is taken into consideration in regulating such firms. Whilst the merits and disadvantages of the individual regulatory strategies are considered, this paper concludes that all regulatory strategies should take into consideration the importance of management responsibilities – both on individual and corporate levels.bank;regulation;risk;command;control

Regulatory Strategies

Over the years, there has been a shift from a wide command-and-control style of supervision whereby the regulator imposes detailed rules with which regulators supervise to one which consists of risk based regulatory strategies. ‘Enforced Self Regulation’, a regulatory strategy whereby negotiation takes places between the State and the individual firms, lies between the command-and-control style of supervision and meta risk regulation in that firms are still required to regulate but according to their own models. It differs from the traditional command-and-control style of bank supervision in that firms and not the regulator, are required to regulate. It is similar to meta-risk regulation in that the individual firm’s model is taken into consideration in regulating such firms. Whilst the merits and disadvantages of the individual regulatory strategies are considered, this paper concludes that all regulatory strategies should take into consideration the importance of management responsibilities – both on individual and corporate levels

Tradable Substitution Rights: Simulation of the Cost-Efficiency of a Nitrogen Reduction in the Pig Finishing Sector

To comply with the European Nitrate Directive, the Flemish manure policy has been elaborated mainly on the base of command and control measures (maximum fertilisation limits etc.). In literature, however, tradable permits are described as a cost efficient and effective instrument. Applied to nutrient emission they might offer an alternative for the current, expensive manure policy. In this publication both policy instruments are compared by means of simulation models. Based on accountacy data from 190 pig finishing farms, it is shown that tradable rights may result in cost savings of over 88%, compared to the most cost efficient command and control model. This result indicates that tradable permits at least need to be considered as a plausible policy instrument for the agricultural sector.tradable permits, agriculture, command and control, nitrogen, linear programming, Livestock Production/Industries, C61, D23, H23, Q58, Q52,

Regulatory strategies

Over the years, there has been a shift from a wide command-and-control style of supervision whereby the regulator imposes detailed rules with which regulators supervise to one which consists of risk based regulatory strategies. ‘Enforced Self Regulation’, a regulatory strategy whereby negotiation takes places between the State and the individual firms, lies between the command-and-control style of supervision and meta risk regulation in that firms are still required to regulate but according to their own models. It differs from the traditional command-and-control style of bank supervision in that firms and not the regulator, are required to regulate. It is similar to meta-risk regulation in that the individual firm’s model is taken into consideration in regulating such firms. Whilst the merits and disadvantages of the individual regulatory strategies are considered, this paper concludes that all regulatory strategies should take into consideration the importance of management responsibilities – both on individual and corporate levels.command,control,regulation,meta,risk

Human Factors Considerations in System Design

Human factors considerations in systems design was examined. Human factors in automated command and control, in the efficiency of the human computer interface and system effectiveness are outlined. The following topics are discussed: human factors aspects of control room design; design of interactive systems; human computer dialogue, interaction tasks and techniques; guidelines on ergonomic aspects of control rooms and highly automated environments; system engineering for control by humans; conceptual models of information processing; information display and interaction in real time environments

Iterative Machine Learning for Precision Trajectory Tracking with Series Elastic Actuators

When robots operate in unknown environments small errors in postions can lead to large variations in the contact forces, especially with typical high-impedance designs. This can potentially damage the surroundings and/or the robot. Series elastic actuators (SEAs) are a popular way to reduce the output impedance of a robotic arm to improve control authority over the force exerted on the environment. However this increased control over forces with lower impedance comes at the cost of lower positioning precision and bandwidth. This article examines the use of an iteratively-learned feedforward command to improve position tracking when using SEAs. Over each iteration, the output responses of the system to the quantized inputs are used to estimate a linearized local system models. These estimated models are obtained using a complex-valued Gaussian Process Regression (cGPR) technique and then, used to generate a new feedforward input command based on the previous iteration's error. This article illustrates this iterative machine learning (IML) technique for a two degree of freedom (2-DOF) robotic arm, and demonstrates successful convergence of the IML approach to reduce the tracking error.Comment: 9 pages, 16 figure. Submitted to AMC Worksho

Building the Infrastructure: The Effects of Role Identification Behaviors on Team Cognition Development and Performance

The primary purpose of this study was to extend theory and research regarding the emergence of mental models and transactive memory in teams. Utilizing Kozlowski et al.’s (1999) model of team compilation, we examine the effect of role identification behaviors and argue that such behaviors represent the initial building blocks of team cognition during the role compilation phase of team development. We then hypothesized that team mental models and transactive memory would convey the effects of these behaviors onto team performance in the team compilation phase of development. Results from 60 teams working on a command and control simulation supported our hypotheses