Combined car-following and unsafe event trajectory simulation using agent based modeling techniques

Maintaining a healthy population with optimal demographic distribution is one of the main stays of an economy. But unfortunately, of late, many developed countries of the world are facing problems of low fertility rate and ageing population. This would eventually have a major impact on the economy. Countries are trying their best to revive the trends and bring back fertility rates to the population sustaining level. But most of these efforts haven't brought back the desired results and despite efforts, many countries continue to face low fertility rate as well as ageing population. Simulation and modelling are one of the best ways to understand population dynamics. Many models have been prepared but they all lack in generality and purpose. In this paper we present a full scale general purpose model for population dynamics, which would use microsimulation and agent based modelling techniques and would assist the modellers and demographers in understanding population dynamics.

Intelligent agents have been regarded as a new notion to build complex software systems. In this paper, we propose an agent-based software development process based on Belief-Desire-Intention (BDI) agent model as a new software development process. The Belief-Desire-Intention (BDI) model has been used as a fundamental ingredient to the new agent-based modeling method. In our agent system proposed here, each agent is made flesh by assigning its own belief, desire and intention. Here we have shown a seamless software development modeling technique consistently based on the BDI model. Even though there are many valuable arguments to define agents beside the BDI model, we currently use the BDI model only to simplify the agent modeling because we try to develop a more realistic agent-based modeling technique. We will extend this work to support other key concepts in agent computing.Here we propose a new approach comparing it with our previous approach to support the BDI agent-based modeling techniques. The previous approach finds intentions, desires and beliefs from two different kinds of use cases - external use cases and internal use cases - and supporting tools. The new approach finds in sequence desires, intentions and beliefs by using not only different kinds of use cases, sequence diagram, activity diagrams, and dataflow diagrams. To prove the usability of our software development process, we also provide a case study to clarify the description of our BDI agent software development process. This paper also introduces a brief structure of a CASE tool that we are currently developing to support the BDI agent software development process.

Understanding complex socio-economic systems is a key problem for commercial organizations. In this chapter we discuss the use of agent-based modelling to produce decision support tools to enhance this understanding. We consider the important aspects of the model creation process which include the facilitation of dialogue necessary to extract knowledge, the building of understanding, and the identification of model limitations. It is these aspects that are crucial in the establishment of trust in a model. We use the example of modelling opinion diffusion within a customer population and its effect on product adoption to illustrate how the agent-based modelling technique can be an ideal tool to create models of complex socioeconomic systems. We consider the advantages compared to alternative, more conventional approaches available to analysts and management decision makers.

Advances on information technology in the past decades have provided new tools to assist scientists in the study of social and natural phenomena. Agent-based modeling techniques have flourished recently, encouraging the introduction of computer simulations to examine behavioral patterns in complex human and biological systems. Real-world social dynamics are very complex, containing billions of interacting individuals and an important amount of data (both spatial and social). Dealing with large-scale agent-based models is not an easy task and encounters several challenges. The design of strategies to overcome these challenges represents an opportunity for high performance parallel and distributed implementation. This chapter examines the most relevant aspects to deal with large-scale agent-based simulations in social sciences and revises the developments to confront technological issues.

Modeling mate choice in a small-scale community: Applying couple simulation in the U.S. and Conambo, Ecuador

Solar photovoltaic (PV) is becoming one of the most significant renewable sources for positive energy district (PED) in Sweden. The lacks of innovative business models and financing mechanisms are the main constraints for PV’s deployment installed in local community. This chapter therefore proposes a peer-to-peer (P2P) business model for 48 individual building prosumers with PV installed in a Swedish community. It considers energy use behaviour, electricity/financial flows, ownerships and trading rules in a local electricity market. Different local electricity markets are designed and studied using agent-based modelling technique, with different energy demands, cost–benefit schemes, and financial hypotheses for an optimal evaluation. This chapter provides an early insight into a vast research space, i.e. the operation of an energy system through the constrained interaction of its constituting agents. The agents (48 households) show varying abilities in exploiting the common PV resource, as they achieve very heterogeneous self-sufficiency levels (from ca. 15% to 30%). The lack of demand side management suggests that social and lifestyle differences generate huge impacts on the ability to be self-sufficient with a shared, limited PV resource. Despite the differences in self-sufficiency, the sheer energy amount obtained from the shared PV correlates mainly with annual cumulative demand.

Modelling Cities as a Collection of TeraSystems – Computational Challenges in Multi-Agent Approach

A methodology employing physics-based and economics-based tools in conjunction with probabilistic treatment is developed to study Personal Air Vehicle business model. In the context of the paper, a business model is a mathematical representation of a service provider business operation. Vehicle concepts and hypothesized metrics such as mobility freedom and ‘value of time’ are embedded in the methodology. Market behavior of the complex transportation environment is captured as part of the equation through Agent-based Modeling and Monte Carlo Simulation techniques. This simulation platform for the transportation environment facilitates the case study of the Atlanta Regional Transportation System. The establishment of this model lays the foundation for creating a robust and adaptive design methodology that allows experts in fields other than aerospace engineering to contribute their expertise towards the realization of this very diverse and dynamic future air transportation system.

Summary Substance flow analysis (SFA) is a frequently used industrial ecology technique for studying societal metal flows, but it is limited in its ability to inform us about future developments in metal flow patterns and how we can affect them. Equation‐based simulation modeling techniques, such as dynamic SFA and system dynamics, can usefully complement static SFA studies in this respect, but they are also restricted in several ways. The objective of this article is to demonstrate the ability of agent‐based modeling to overcome these limitations and its usefulness as a tool for studying societal metal flow systems. The body of the article summarizes the parallel implementation of two models—an agent‐based model and a system dynamics model—both addressing the following research question: What conditions foster the development of a closed‐loop flow network for metals in mobile phones? The results from in silico experimentation with these models highlight three important differences between agent‐based modeling (ABM) and equation‐based modeling (EBM) techniques. An analysis of how these differences affected the insights that could be extracted from the constructed models points to several key advantages of ABM in the study of metal flow systems. In particular, this analysis suggests that a key advantage of the ABM technique is its flexibility to enable the representation of societal metal flow systems in a more native manner. This added flexibility endows modelers with enhanced leverage to identify options for steering metal flows and opens new opportunities for using the metaphor of an ecosystem to understand metal flow systems more fully.

A social model based on customers’ profiles for analyzing the churning process in the mobile market of data plans

Networks can be observed both within financial institutions and in the interaction between these institutions and the financial industry as a whole. Dealing with these networks and identifying their critical channels presents numerous challenges to strategic, operational and risk decision-makers. Many novel approaches show promise, but have been difficult to scale due to a lack of computing power. Advances in technology however enable financial institutions to implement and use these untapped methods for strategic, operational and risk management. After a brief review of the taxonomy and a presentation of recent methods to study the intrinsic risks, the authors present three distinct modern approaches to dealing with network modeling and their respective management approaches. Neural networks, agent-based modeling and process mining techniques are particularly highlighted here, supported by a range of use cases. Finance professionals are encouraged to review their approaches to dealing with network complexity in the light of recent technological advances in using these methods.

Agent-based modelling of wind damage processes and patterns in forests

This paper discusses devising a methodology for developing a heuristic approach for planning authorities and policy makers to investigate the integration of electric mobility charging infrastructure in metropolitan cities, particularly in the UK. This study is a part of a PhD research project; it presents a part of its overall methodology, which will be employed in a smaller-scale pilot project to obtain initial findings. An agent-based modelling and simulation (ABMS) technique is proposed to represent the phenomenon and analyze it. This study covers the development of the model, emphasizing how it would reflect Electric Vehicles (EVs) current users' behaviours and their charging habits. The aim of the PhD research is to examine whether the current electric-mobility charging infrastructure can support current users and whether it can accommodate future potential users or if the planning authorities and policy makers need to forecast and plan for more charging points. This in return shall potentially provide a better accessibility to e-mobility and support its market, partly by better informed location decision making.

In probabilistic risk assessment (PRA) of nuclear power plants (NPPs), human reliability analysis (HRA) is conducted to identify potential human failure events that could contribute to risk scenarios and estimate human error probabilities. Lessons learned from the 2011 Fukushima Daiichi NPP accident underscored that for PRA, it is critical to model external control room (Ex-CR) human actions. The state-of-practice HRA methods, historically developed for the main control room HRA, are limited in capturing the unique nature of Ex-CR human actions, such as location dependence (in addition to the time dependence) of human actions and spatiotemporal interactions of human performance with the surrounding physical environments, for instance, hazard propagation. To advance the Ex-CR HRA in the context of the fire PRA for NPPs, the authors’ team developed a simulation-based fire crew performance model using an agent-based modeling (ABM) technique. The ABM fire crew simulation was coupled with a fire progression model through a spatiotemporal interface using a geographic information system. This paper focuses on the validation of the ABM simulation, which is the key requirement for the simulation-based Ex-CR human performance model to be utilized in PRA. The existing validation approach, initially developed for physical models in the fire PRA of NPPs, is extended for validation of the simulation-based Ex-CR human performance model. Model uncertainty is used as a measure of model validity, which facilitates the incorporation of the validation result into the PRA. The degree of the model uncertainty is characterized by a lognormal error model whose parameters are quantified based on a pairwise comparison between empirical data and model predictions. The proposed validation approach is demonstrated using a case study of the fire PRA of NPPs. This study makes two research contributions: (1) it is the first to validate the simulation-based Ex-CR human performance model against empirical human performance data and incorporate the validation result into the PRA of NPPs, and (2) this study, for the first time, conducts a controlled experimental test to collect empirical data for fire crew performance at NPPs.

Airport slot allocation is a combinatorial allocation problem involving different complex and autonomous systems. Nowadays, airport slots are allocated in a two-stage process: primary allocation is performed according to a set of administrative rules and for each airport independently, while secondary allocation is based on trading mechanisms. Several studies have raised inefficiencies in these processes. To enhance the airport slot allocation process we use an auction-based market. More specifically, we present an airport slot allocation mechanism based on a price-setting auction that has been implemented and evaluated by means of Agent-Based Modelling (ABM) and simulation techniques. The solutions obtained using our approach are compared and assessed with the ones obtained using linear programing, showing that market mechanisms can be an efficient alternative to the current administrative procedure.