Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
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Displaying 3 of 3 results travel patterns clear
This model was created to investigate the potential impacts of large-scale recreational and transport-related physical activity promotion strategies on six United Nations Sustainable Development Goals (SDGs) related outcomes—road traffic deaths (SDG 3), transportation mode share (SDG 9), convenient access to public transport, levels of fine particulate matter, and access to public open spaces (SDG 11), and levels of carbon dioxide emissions (SDG 13)—in three cities designed as abstract representations of common city types in high-, middle-, and low-income countries.
We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.
The core algorithm is an agent-based model, which simulates travel patterns on a network based on microscopic decision-making by each traveler.