Abstract

International audience; City systems, consisting of the various social and technical infrastructures required for urban areas to function, are facing major challenges in the coming decades as global urbanization and the pressure on resource efficiency and sustainability continue. Agent-based simulation and modelling techniques enable us to study these systems from various levels of abstraction looking at actors as well as system level perspectives, and are particularly suited to understand the dynamics of underlying structures and experiment with various scenarios and the effect of local decisions on emerging system properties. This special issue aims to showcase innovative use of agent-based modelling (ABM) and multi-agent system (MAS) approaches for effective decision support regarding urban innovations in fields linked with urban development and to explore and identify how researchers in different disciplines integrate their knowledge through agent models. We are inviting researchers from across a wide range of disciplines (including computer science, physics, engineering, economics, sociology and others) to submit papers to this special issue that exhibit state-of the art innovation in ABM/MAS applied to cities. This innovation may come in the form of computational, conceptual, analytical, participatory or epistemological advances for a range of aims and motivations associated with the challenge of combining competitiveness and sustainable urban development in city systems. Possible topics include, but are not limited to, the following:[...]

Abstract

The transport, electricity and telecommunication systems, also known as utilities, are under pressure from disruptive technologies, climate change and even unexpected health disasters. Questions related to demand management and safeguarding the functioning of the system are an important part of handling these pressures. In terms of road transport more specifically, the practices currently in use have been unsuccessful in flattening the demand curve or shifting the demand to more sustainable and space-efficient modes of travel. Therefore, the need for new input in the transport sector regarding demand management is higher than ever before. This report is intended to provide new insights for the transport sector based on the practices and methods for managing fluctuating demand found in other sectors, which can be translated into the following research question: What can the road transport sector learn about demand management practices from the electricity and telecom sectors? The analytical framework used for data collection and analysis is based on and combines the socio-technical theory of large technical systems (LTS) with the multi-level perspective (MLP) on sustainable transition into the infrastructure lifecycle model (ILM) introduced by Bolton and Foxon (2015). The findings are divided into three sections: road transport, electricity and telecom, and a matrix summarizing the identified practices and tools in use is provided at the end of each section. The concluding section is structured into specific learnable moments/new insights, providing an overview and discussion of all three systems in parallel with the help of the ILM. These moments include real-time monitoring and interventions, activating end users to make better-informed decisions, and public-private participation in planning and development. The report concludes with suggestions for future research. "p"QC 20200828

Abstract

What is a suitable modelling approach for socio-technical systems? The answer to this question is of great importance to decision makers in large scale interconnected network systems. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level jungle. Models to support such an actor should be able to capture both the physical and social reality of the system, their interactions with one another and the external dynamic environment. Moreover, they must allow users to experiment with changes in both the physical and the social network configuration. To deal with these challenges a generic agent-based modelling framework for socio-technical systems is developed in this thesis. The cornerstone of the framework is a shared language formalised in an ontology, which forms the interface needed to bring different elements of the system (both social and physical) together, to interconnect different models and ensure interoperability. The re-usability of building blocks helps modellers build new models more efficiently. The models developed with the new framework are shown to offer valuable decision support in case studies of an oil refinery supply chain and an intermodal freight hub.

Abstract

The sustainability of Short Sea Shipping (SSS) is central to a clean, safe, and efficient European Union (EU) transport system. We report on key challenges for advancing reliability, quality, and safety, and removing unnecessary costs and delays at SSS hubs, with a particular focus on Cyprus and the Eastern Mediterranean. Specifically, we consider the effect of port-2-port (P2P) communication on port efficiency by investigating the factors influencing the various waiting times at the Port of Limassol, both from a qualitative and a quantitative perspective. The qualitative results are based on the views of key stakeholders involved in the port call process. The quantitative analysis relies on data from over 8000 port calls during 2017&ndash 2018, which are analyzed with respect to ship type, port of origin, and shipping agent. The calculated Key Performance Indicators (KPIs) include arrival punctuality, berth waiting, and berth utilization. The analysis clearly reveals considerable variation in agent performance regarding the KPIs, suggesting a lack of attention to the social aspect of a port&rsquo s socio-technical system. We propose measures for improving agent performance based on the principles of Port Collaborative Decision Making (PortCDM), including P2P communication, data sharing and transparency among all involved in a port call process including the agents, and open dissemination of agent-specific KPIs. Document type: Article

Abstract

Due to the continuous increment in complexity of the socio-technical systems, decision makers call for new methods which are able to support timely as well as accurate decision-making related to resilience management. The current methods tend to be polarized on: efficiency-thoroughness forcing decision makers in making decisions on the base of resource availability instead of the problem to be solved. This paper presents a new fast-forward, cost-effective, and thorough enough framework to quantify resilience of a complex socio-technical system. The approach extends the functional resonance analysis method (FRAM) with a numerical method for the quantification of the analysis (Q-FRAM). In particular, it has been extended and operationalized the qualitative concepts of functional variability and dumping capacities into a method in which key performance indicators are derived from the model and aggregated into four indicators representing the FRAM resilience cornerstones (anticipate, respond, monitor, learn) through a bottom-up hierarchical approach. Finally, the four indicators are composed in a unique system resilience index that expresses the total variability present in the system at instant t . A numerical example of the use of the framework is provided together with a validation based on a comparison of the proposed approach with the current landscape.

Abstract

Greater automation of air traffic control (ATC) could reduce aviation's climate change impacts, but improvements predicted long ago have been slow to happen. This resistance to ATC modernisation is framed as an issue of lock-in, and the detailed case study described here enables an analysis of the factors involved in slowing change. Although the classic lock-in effects of ‘increasing returns’ and ‘network externalities’ are important, a major barrier to modernisation is due to the political and organisational challenges of coordinating change across a large, complex socio-technical system. However, lock-in effects are crucial with respect to the perceived increasing returns accrued from experience with manual ATC operations, and the difficulty of quantifying the risks of automation (particularly as regard the use of complex software) is a major barrier to further improvements. Overcoming this obstacle to further automation depends on finding ways to test and operate new ATC software and procedures without compromising safety. Document type: Article