Abstract: Agent based modelling has been widely accepted as a promising tool for urban planning purposes thanks to its capability to provide sophisticated insights into the social behaviours and the interdependencies that characterise urban systems. In this paper, we report on an agent based model, called TransMob, which explicitly simulates the mutual dynamics between demographic evolution, transport demands, housing needs and the eventual change in the average satisfaction of the residents of an urban area. The ability to reproduce such dynamics is a unique feature that has not been found in many of the like agent based models in the literature. TransMob, is constituted by six major modules: synthetic population, perceived liveability, travel diary assignment, traffic micro-simulator, residential location choice, and travel mode choice. TransMob is used to simulate the dynamics of a metropolitan area in South East of Sydney, Australia, in 2006 and 2011, with demographic evolution. The results are favourably compared against survey data for the area in 2011, therefore validating the capability of TransMob to reproduce the observed complexity of an urban area. We also report on the application of TransMob to simulate various hypothetical scenarios of urban planning policies. We conclude with discussions on current limitations of TransMob, which serve as suggestions for future developments.
Abstract: Prior exploration is an instructional strategy that has improved performance and understanding in system-dynamics-based simulators, but only to a limited degree. This study investigates whether model transparency, that is, showing users the internal structure of models, can extend the prior exploration strategy and improve learning even more. In an experimental study, participants in a web-based simulation learned about and managed a small developing nation. All participants were provided the prior exploration strategy but only half received prior exploration embedded in a structure-behavior diagram intended to make the underlying model’s structure more transparent. Participants provided with the more transparent strategy demonstrated better understanding of the underlying model. Their performance, however, was the equivalent to those in the less transparent condition. Combined with previous studies, our results suggest that while prior exploration is a beneficial strategy for both performance and understanding, making the model structure transparent with structure-behavior diagrams is more limited in its effect.
Abstract: Waste management is a complex task involving numerous waste fractions, a range of technological treatment options, and many outputs that are circulated back into society. A systematic, interdisciplinary systems management framework was developed to facilitate the planning, implementation, and maintenance of sustainable waste systems. It aims not to replace existing decision-making approaches, but rather to enable their integration to allow for inclusion of overall sustainability concerns and address the complexity of solid waste management. The framework defines key considerations for system design, steps for performance monitoring, and approaches for facilitating continual system improvements. It was developed by critically examining the literature to determine what aspects of a management framework would be most effective at improving systems management for complex waste systems. The framework was applied to food waste management as a theoretical case study to exemplify how it can serve as a systems management tool for complex waste systems, as well as address obstacles typically faced in the field. Its benefits include the integration of existing waste system assessment models; the inclusion of environmental, economic, and social priorities; efficient performance monitoring; and a structure to continually define, review, and improve systems. This framework may have broader implications for addressing sustainability in other disciplines.
Abstract: Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidate inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. Finally, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.
Abstract: Modern society is facing great challenges due to pollution and increased carbon dioxide (CO2) emissions. As part of solving these challenges, the use of renewable energy sources and electric vehicles (EVs) is rapidly increasing. However, increased dynamics have triggered problems in balancing energy supply and consumption demand in the power systems. The resulting uncertainty and unpredictability of energy production, consumption, and management of peak loads has caused an increase in costs for energy market actors. Therefore, the means for studying the balancing of local smart grids with EVs is a starting point for this paper. The main contribution is a simulation-based approach which was developed to enable the study of the balancing of local distribution grids with EV batteries in a cost-efficient manner. The simulation-based approach is applied to enable the execution of a distributed system with the simulation of a local distribution grid, including a number of charging stations and EVs. A simulation system has been constructed to support the simulation-based approach. The evaluation has been carried out by executing the scenario related to balancing local distribution grids with EV batteries in a step-by-step manner. The evaluation results indicate that the simulation-based approach is able to facilitate the evaluation of smart grid– and EV-related communication protocols, control algorithms for charging, and functionalities of local distribution grids as part of a complex, critical cyber-physical system. In addition, the simulation system is able to incorporate advanced methods for monitoring, controlling, tracking, and modeling behavior. The simulation model of the local distribution grid can be executed with the smart control of charging and discharging powers of the EVs according to the load situation in the local distribution grid. The resulting simulation system can be applied to the study of balancing local smart grids with EV batteries. Based on the evaluation results, it is estimated that the simulation-based approach can provide an essential, safe, and cost-efficient method for the evaluation of complex, critical cyber-physical systems, such as smart grids.
Abstract: Italian New Public Management (NPM) has been mainly characterized by a political orientation toward power decentralization to local governments and privatization of public companies. Nowadays, local utilities in Italy are often run by joint stock companies controlled by public agencies such as Regional and Municipal Administrations. Due to this transformation, these companies must comply with a set of diverse expectations coming from a wide range of stakeholders, related to their financial, competitive and social performance. Such fragmented governance increases the presence of “wicked” problems in the decision-making sphere of these entities. Given this multi-level governance structure, how do these agents influence public services performance? In recent years, coordination and inter-institutional joint action have been identified as possible approaches for dealing with governance fragmentation and wicked problems deriving from it. How can we adapt a performance management perspective in order to help us reform the system and so have a better collaboration between the stakeholders involved? In order to address and discuss these research questions, a case study will be developed. The case concerns AMAT, the local utility providing the public transportation service in the Municipality of Palermo (Italy). The result of this study is a dynamic model including a set of performance indicators that help us in understanding the impact of the governing structure on the system’s performance.