modelling and simulation for major incidents

In recent years, there has been a rise in Major Incidents with big impact on the citizens health and the society. Without the possibility of conducting live experiments when it comes to physical and/or toxic trauma, only an accurate in silico reconstruction allows us to identify organizational solutions with the best possible chance of success, in correlation with the limitations on available resources (e.g. medical team, first responders, treatments, transports, and hospitals availability) and with the variability of the characteristic of event (e.g. type of incident, severity of the event and type of lesions). Utilizing modelling and simulation techniques, a simplified mathematical model of physiological evolution for patients involved in physical and toxic trauma incident scenarios has been developed and implemented. The model formalizes the dynamics, operating standards and practices of medical response and the main emergency service in the chain of emergency management during a Major Incident

Current capabilities, requirements and a proposed strategy for interdependency analysis in the UK

The UK government recently commissioned a research study to identify the state-of-the-art in Critical Infrastructure modelling and analysis, and the government/industry requirements for such tools and services. This study (Cetifs) concluded with a strategy aiming to bridge the gaps between the capabilities and requirements, which would establish interdependency analysis as a commercially viable service in the near future. This paper presents the findings of this study that was carried out by CSR, City University London, Adelard LLP, a safety/security consultancy and Cranfield University, defense academy of the UK

The use of simulation in the design of a road transport incident detection algorithm

Automatic incident detection is becoming one of the core tools of urban traffic management, enabling more rapid identification and response to traffic incidents and congestion. Existing traffic detection infrastructure within urban areas (often installed for traffic signal optimization) provides urban traffic control systems with a near continuous stream of data on the state of traffic within the network. The creation of a simulation to replicate such a data stream therefore provides a facility for the development of accurate congestion detection and warning algorithms. This paper describes firstly the augmentation of a commercial traffic model to provide an urban traffic control simulation platform and secondly the development of a new incident detection system (RAID-Remote Automatic Incident Detection), with the facility to use the simulation platform as an integral part of the design and calibration process. A brief description of a practical implementation of RAID is included along with summary evaluation results

Traffic-responsive urban network control using multivariable regulators

The paper presents the philosophy, the aim, the development, the advantages, and the potential shortcomings of the TUC (Traffic-responsive Urban Control) strategy. Based on a store-and-forward modeling approach and using well-known methods of the Automatic Control Theory, the approach followed by TUC designs (off-line) and employs (on-line) a multivariable regulator for traffic-responsive co-ordinated network-wide signal control. Simulation investigations are used to demonstrate the efficiency of the proposed approach. Based on the presented investigations, summarising conclusions are drawn and future work is outlined

Microsimulation models incorporating both demand and supply dynamics

There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers’ decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers’ choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space–time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamic

STOP-IT: strategic, tactical, operational protection of water infrastructure against cyberphysical threats

Water supply and sanitation infrastructures are essential for our welfare, but vulnerable to several attack types facilitated by the ever-changing landscapes of the digital world. A cyber-attack on critical infrastructures could for example evolve along these threat vectors: chemical/biological contamination, physical or communications disruption between the network and the supervisory SCADA. Although conceptual and technological solutions to security and resilience are available, further work is required to bring them together in a risk management framework, strengthen the capacities of water utilities to systematically protect their systems, determine gaps in security technologies and improve risk management approaches. In particular, robust adaptable/flexible solutions for prevention, detection and mitigation of consequences in case of failure due to physical and cyber threats, their combination and cascading effects (from attacks to other critical infrastructure, i.e. energy) are still missing. There is (i) an urgent need to efficiently tackle cyber-physical security threats, (ii) an existing risk management gap in utilities’ practices and (iii) an un-tapped technology market potential for strategic, tactical and operational protection solutions for water infrastructure: how the H2020 STOP-IT project aims to bridge these gaps is presented in this paper.Postprint (published version

Automated post-fault diagnosis of power system disturbances

In order to automate the analysis of SCADA and digital fault recorder (DFR) data for a transmission network operator in the UK, the authors have developed an industrial strength multi-agent system entitled protection engineering diagnostic agents (PEDA). The PEDA system integrates a number of legacy intelligent systems for analyzing power system data as autonomous intelligent agents. The integration achieved through multi-agent systems technology enhances the diagnostic support offered to engineers by focusing the analysis on the most pertinent DFR data based on the results of the analysis of SCADA. Since November 2004 the PEDA system has been operating online at a UK utility. In this paper the authors focus on the underlying intelligent system techniques, i.e. rule-based expert systems, model-based reasoning and state-of-the-art multi-agent system technology, that PEDA employs and the lessons learnt through its deployment and online use

GARTEUR Helicopter Cooperative Research

This paper starts with an overview about the general structure of the Group for Aeronautical Research and Technology in EURope (GARTEUR). The focus is on the activities related to rotorcraft which are managed in the GARTEUR Helicopter Group of Responsables (HC GoR). The research activities are carried out in so-called Action Groups. Out of the 5 Action Groups which ended within the last four years results generated in the Helicopter Action Groups HC(AG14) “Methods for Refinement of Structural Dynamic Finite Element Models”, HC(AG15) “Improvement of SPH methods for application to helicopter ditching” and HC(AG16) “Rigid Body and Aeroelastic Rotorcraft-Pilot Coupling” are briefly summarized

Variable speed limits: conceptual design for Queensland practice

Variable Speed Limits (VSL) is an Intelligent Transportation Systems (ITS) control tool which can enhance traffic safety and which has the potential to contribute to traffic efficiency. Queensland's motorways experience a large volume of commuter traffic in peak periods, leading to heavy recurrent congestion and a high frequency of incidents. Consequently, Queensland's Department of Transport and Main Roads have considered deploying VSL to improve safety and efficiency. This paper identifies three types of VSL and three applicable conditions for activating VSL on for Queensland motorways: high flow, queuing and adverse weather. The design objectives and methodology for each condition are analysed, and micro-simulation results are presented to demonstrate the effectiveness of VSL