Related papers: Integrated Agent-based Microsimulation Framework f…
Efficient public transport systems are crucial for sustainable urban development as cities face increasing mobility demands. Yet, many public transport networks struggle to meet diverse user needs due to historical development, urban…
Technological advancements have brought increasing attention to Automated Mobility on Demand (AMOD) as a promising solution that may improve future urban mobility. During the last decade, extensive research has been conducted on the design…
An agent-based model with interacting low frequency liquidity takers inter-mediated by high-frequency liquidity providers acting collectively as market makers can be used to provide realistic simulated price impact curves. This is possible…
We tackle the problem of evaluating the impact of different operation policies on the performance of a microtransit service. This study is the first empirical application using the stable matching modeling framework to evaluate different…
Nowadays, universities and companies have a huge need for simulation and modelling methodologies. In the particular case of traffic and transportation, making physical modifications to the real traffic networks could be highly expensive,…
The diffusion of electric vehicles (EVs) is considered an effective policy strategy to meet greenhouse gas reduction targets. For large-scale adoption, however, demand-side oriented policy measures are required, based on consumers transport…
The distributional impacts of congestion pricing have been widely studied in the literature and the evidence on this is mixed. Some studies find that pricing is regressive whereas others suggest that it can be progressive or neutral…
Simulative and scenario-based testing are crucial methods in the safety assurance for automated driving systems. To ensure that simulation results are reliable, the real world must be modeled with sufficient fidelity, including not only the…
As zero-emission zones emerge in European cities, fleet operators are shifting to electric vehicles. To maintain their current operations, a clear understanding of the charging infrastructure required and its relationship to existing power…
This work outlines the modeling steps for developing a tool aimed at supporting policymakers in guiding policies toward more sustainable wheat production. In the agricultural sector,policies affect a highly diverse set of farms, which…
This article proposes a fundamental methodological shift in the modelling of policy interventions for sustainability transitions in order to account for complexity (e.g. self-reinforcing mechanism arising from multi-agent interactions) and…
Agent-based modeling (ABM) has emerged as a powerful tool in social policy-making and socio-economics, offering a flexible and dynamic approach to understanding and simulating complex systems. While traditional analytic methods may be less…
This paper demonstrates the use of the Multi-Agent MicroServices (MAMS) architectural style through a case study based around the development of a prototype traffic simulation in which agents model a population of individuals who travel…
Agent technology is a software paradigm that permits to implement large and complex distributed applications. In order to assist the development of multi-agent systems, agent-oriented methodologies (AOM) have been created in the last years…
In this paper, the technical requirements to perform a cost-benefit analysis of a Demand Responsive Transport (DRT) service with the traffic simulation software MATSim are elaborated in order to achieve the long-term goal of assessing the…
This report presents results from an M1 internship dedicated to agent-based modelling and simulation of daily mobility choices. This simulation is intended to be realistic enough to serve as a basis for a serious game about the mobility…
Simulation plays a crucial role in assessing autonomous driving systems, where the generation of realistic multi-agent behaviors is a key aspect. In multi-agent simulation, the primary challenges include behavioral multimodality and…
Over the past decade, there has been a surge of interest in the transport community in the application of agent-based simulation models to evaluate flexible transit solutions characterized by different degrees of short-term flexibility in…
In the research of Intelligent Transportation Systems (ITS), traffic simulation is a key procedure for the evaluation of new methods and optimization of strategies. However, existing traffic simulation systems face two challenges. First,…
Multi-agent trajectory forecasting in autonomous driving requires an agent to accurately anticipate the behaviors of the surrounding vehicles and pedestrians, for safe and reliable decision-making. Due to partial observability in these…