SUMMIT: A multi-modal agent-based co-simulation of urban public transport with applications in contingency planning

An Analysis of Multi Agent Systems Agent Based Programming

“…BDI models are frequently preferred by domain experts as they offer a simpler means for them to express their expertise and also facilitate the explanation of behavior. Othman et al [6] present a thorough investigation and evaluation of techniques for integrating BDI models into ABS. The authors underscore the benefits of BDI models in the implementation of descriptive agents, which possess more intricate models than reactive agents.…”

Exploring the Applications of Agent-Based Modeling in Transportation

“…As for the transport operating by road, a series of ABM applications have focused on presenting a robust model for tackling cross-docking challenges, thereby streamlining logistics operations [21], facilitating simulations to gauge the ramifications of introducing shared bikes and e-scooters on existing travel modalities [22], scrutinizing the effects of automated mobility-on-demand services on the broader public transportation landscape [23], experimenting with the significance of traffic information exchange in ameliorating traffic congestion [24], conducting a comparative analysis between two operational strategies of public transport services, namely fixed-route transit (FRT) and demand-responsive transport (DRT) [25], employing simulations to bolster urban public transport systems, with direct implications for contingency planning [26], attaining cooperation in road networks [27], simulating the diffusion of information between road freight transport agents [28]. Another area of research connected to road transportation is related to the risks associated with this type of transportation.…”

“…The authors' investigation into public transport ridership during the COVID-19 pandemic furnishes compelling evidence, wherein the implementation of a 1.5-m social distance policy results in the Washington DC metro system operating at a mere 18% of its total capacity. The imposition of a more stringent 2-m social distance policy further exacerbates this capacity contraction, reducing it to a mere 10% [26]. Given the profound diminution in capacity witnessed in single-destination public transportation contexts, Moore et al [40] proffer a proactive solution by advancing a solution to address passenger seat assignments.…”