|Some information about my research interests can be found in this presentation and on this poster.|
|Creating an Artificial Hotspot Laboratory Prototype for Investigating HGV Hotspot Incidences|
|Funded internally by D^3 RPA Discipline Bridging Fund + ADAC (£11.022)|
|In this project we want to explore how we can take advantage of the multitude of collected data streams related to HGV incidents and the information/knowledge derived from these data streams after data analysis. Such data is collected by our industrial partner Microlise whose incident black boxes are installed in over 25% of the UK HGVs, capturing the driving behaviour of more than 90,000 drivers. Microlise is currently working with us on an Innovate UK project (VEDAT: 101938) which aims to develop a method for identify incidence hotspot locations from big incidence data sets. The dataset we are working with contains three month worth of data (1.2 million data points) about different types of HGV driving behaviour incidences: contextual speeding, speeding, harsh braking, harsh corners. These incidences can be traced back to individual drivers. We aim to develop an Artificial Hotspot Lab (AHL) prototype that will allow us to simulate different types of HGV drivers and their driving behaviours. With such a simulator (a what-if analysis tool) we could study the potential impact of driver personality on hot spot evolution with or without using innovative guidance systems as the one planned to be developed by Microlise which will inform drivers about upcoming hazards. For developing the AHL we will use an Agent-Based Modelling (ABM) and simulation approach.|
|In this project I am the PI. The COIs are Bob John (UoN: CompSci), Grazziela Figueredo (UoN: ADAC), and Mohammad Mesgarpour (Microlise). The research is conducted by Grazziela Figueredo (UoN CompSci). The duration of the project is 3 month.|
|Agent-Based Modelling for Simulating Peacebuilding: A Feasibility Study|
|Funded internally (£5.100) [official website]|
|This project is about developing a framework for building agent-based simulation models of conflict-affected areas using Software Engineering (the unified modelling language - UML) for the conceptual modelling process. This framework will allow us to study how individuals in conflict-affected regions change their perceptions towards great powers and their behaviours as a result of international peacebuilding efforts - with a focus on those conducted by China. From a technical perspective we are particularly interested in developing a novel way of considering opinion dynamics as well as polarisation and including environmental psychology within our object oriented social simulation models.|
We will test our ideas using a case study approach. The case study is based on empirical data from a study conducted by Hirono (2011). This study investigates the perceptions and behaviours of the Sudanese and South Sudanese government and people towards Chinese immigrants who engage in peacebuilding efforts. It is also of interest to observe how these perceptions modify overtime, as the environment changes. The objective of the simulation is to provide insights into research questions such as: (1) How do people in Sudan and South Sudan perceive China's peacebuilding policy and practices? (2) How do such perceptions and the political/social/economic conditions of Sudan and South Sudan lead to particular behaviours that make up the Sudanese and South Sudanese' relations with China? (3) How and why do such perceptions and behaviours change over time?
The figure below shows schematically the elements of the interactive process of our SimPB framework. These include establishing archetypes, creating general agent templates using UML, creating specific agent objects that are then integrated and cross linked within the simulation environment, running experiments, and analysing results.
|The PI in this project is Miwa Hirono (UoN: Politics). The COIs in this project are Peer-Olaf Siebers (UoN: CompSci) and Anya Skatova (UoN: Psychology). The research is conducted by Grazziela Figueredo (UoN CompSci). Academic support is provided by Lisa Siebers (NTU: Business School). The duration of the project is 3 month.|
|Sustaining Urban Habitats: An Interdisciplinary Approach|
|Leverhulme RP2013-SL-015 (£1.75M with an additional £1.65M Institutional Support) [Official Website]|
|The aim of this programme is to develop a distinctively interdisciplinary approach to producing and evaluating scenarios for sustainable living in urban habitats. With two growth cities in China (Chengdu, Shanghai) and two transition cities in Europe (Nottingham, Stuttgart) as our empirical focus, we will explore ways of combining environmental and economic modelling with social and cultural ethnographic work to illuminate: realistic measures of urban sustainability and options for improving resilience and resource flows (Theme #1); patterns of consumption by different groups and social perspectives on measures and scenarios for improving sustainability (Theme #2); factors shaping economic activity and migration, and prospects for balancing economic and social capital with environmental capital (Theme #3); effective ways of managing the different forms of data from #1 to #3 to develop appropriate indicators of sustainability (Theme #4); minimising resource demands in response to underlying stimuli and constraints (Theme #5); the role of public policies and policy-maker perspectives on the indicators and scenarios that we develop (Theme #6).|
|The PI on this project is Darren Robinson. I am one of the 9 CI's and together with Paul Nathanail I am looking after Theme #5 (Modelling and Optimisation).|
|Test Driven Object Oriented Simulation Modelling|
|Funded internally (£1.500)|
|Agile Software Development (ASD) has been a recent revolution in program design. ASD comprises a group of software development methods based on iterative and incremental improvement. Extreme Programming (XP) is one of the methods that falls into this category. XP intends to improve software quality and responsiveness to changing customer requirements and promotes Test Driven Development (TDD) as one of the practices. TDD (unit testing) forces a programmer to take a different view of the system by writing (and thinking about) the test cases before writing the actual unit code. The idea is illustrated in the diagram below [Source: Wikipedia].|
To our knowledge this kind of approach has never been applied to developing component based simulation models where researchers/practitioners often work with predefined components (design patterns) rather than coding methods. Moreover, an interesting aspect to consider is that different simulation methods have different design philosophies. Discrete Event Simulation (DES) focuses on describing the processes and operations while Agent-Based Simulation (ABS) focuses on designing individual entities and their behaviours and interaction. Therefore another open research direction to take would be to investigate whether the test driven development is applicable in the same way under both simulation modelling philosophies.
On this project I share the investigator role with Ender Özcan. The research is conducted by Asta Shahriar
|Future Energy Decision Making for Cities - Can Complexity Science Rise to the Challenge?|
|EPSRC EP/G05956X/1 Project Website|
The research addresses a key challenge for energy sustainability - how can individual UK cities play their vital role in the implementation of ambitious future UK energy sustainability policies between now and 2020, whilst mitigating conflicts with the local imperatives that until now have dominated local government decision making? There are many different actors/key stakeholders (and legislation) involved in decision making processes that interact/influence each other in a non linear way. It is common practice to model only a subset of the actors involved in the decision making process. However, to get a realistic representation of the real system and its decision making processes we need to model the decision makers (politicians and senior local government personnel) on the one hand and the people influencing the decision making process (energy companies and their executives, activity groups and end users) on the other hand.
We will deploy agent-based modelling and simulation to deliver models that enable cities to define their current energy situation and then reach balanced decisions in their future energy planning, implementing UK sustainability targets. The project work will also involve efforts to relate and, where possible, integrate these agent-based models with dynamical network models of the evolving energy supply-demand network developed be our collaborators at Leeds University.
I am a co-investigator on this project. The research is conducted by Dr Tao Zhang
|Modelling and Analysing the Cargo Screening Process|
The efficiency of current cargo screening processes is unknown as no benchmarks exists against which they could be measured (% detected vs. % missed). Some manufacturer benchmarks exist for individual sensors which have been tested under laboratory conditions but we have not found any benchmarks that take a holistic view of the screening procedures assessing a combination of sensors and also taking operator variability into account.
Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making (e.g. interpreting sensor signals) and operator compliance to rules (e.g. when operating with equipment) play a vital role. For such systems more advanced assessment methods need to be used, taking into account that the cargo screening process is of a dynamic and stochastic nature.
We are proposing to design a plug and play software tool (cargo screening system simulator) that will map the right technology and manpower to the right commodity / threat combination. System simulation can help to understand the processes currently in place and show the consequences of changes to these processes over time. The tool will enable the optimisation of resources (equipment, manning) and processes (job organisation, interoperability of equipment, teamwork, communication, data flow) and allow to evaluate the integration of new sensor technology and how they will improve detection efficiency.
|A Multi-Agent Simulation of Retail Management Practices|
Our previous project is part of an IDEAS Factory Network Project which investigates the role of management practices in closing the productivity gap. Our task in Nottingham is to develop a tool that helps to understand and predict the impact of different management practices on retail store productivity. After an intensive review of the literature we have decided to use agent-based modelling and simulation to support our investigations. In agent-based simulation models a complex system is represented by a collection of agents that are designed to mimic the behaviour of their real world counterparts and are programmed to follow some often quite simple behaviour rules. Macro behaviour is not modelled but it emerges from the micro decisions of the individual agents (Pourdehnad et al., 2002). Through interaction of agents with each other and their environment the simulation produces complex collective behaviour patterns.
There has been a fair amount of modelling and simulation of operational management practices, but people management practices have often been neglected although research suggests that they crucially impact upon an organization's performance (Birdi et al., 2008). One reason for this neglect relates to the key component of people management practices, an organisation's people, who may often be unpredictable in their individual behaviour.
In our project we focus on simulating various in-store scenarios grounded in empirical case studies with a leading UK retailer. We investigate if agent-based modelling and simulation can help us with assessing the impact of people management practices on customer satisfaction, under consideration of external stimulation attributable to the word of mouth and internal stimulation triggered by memory of one's own previous shopping experiences in relation to the performance of a service-oriented retail department.
To achieve this aim we have adopted a case study approach using applied research methods to collect both qualitative and quantitative data. This has enabled us to acquire a valid and reliable understanding of how the real system operates, revealing insights into the working of the system as well as the behaviour of and interactions between the different individuals and their complementary roles within the retail department. Using this knowledge and data, we have applied agent-based modelling to devise a functional representation of the case study departments. By executing the simulation models we can run experiments to investigate the effects of different management scenarios.
We have presented our work at all major annual simulation conferences and have found that interest in the research area is steadily growing. Developing capabilities in modelling human behaviour and performance becomes more and more relevant for business and organisations but also in areas like prevention of terrorism, homeland security, and emergency responses.