United States Department of Transportation
i
Multi-agent Simulation-based Virtual Test Bed Ecosystem: MATSim- NYC [supporting datasets]
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2020-10-12
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By He, Yueshuai
[PDF-112.60 KB]
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Alternative Title:Code for MATSim-NYC project
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Abstract:One of the missions of C2SMART is to help cities around the country better understand the transferability of transportation technologies. For this purpose, two yearlong projects were initiated from 2018 – 2020 to initiate a new virtual test bed ecosystem: (1) 2018 – 2019: Phase I: Open Source Multi-Agent Virtual Simulation Testbed and (2) 2019 – 2020: Phase II: Development and Tech Transfer of Multi-Agent Simulation Testbed. This report covers the findings of both years’ projects. The objective of these two projects is to develop an initial architecture and virtual test bed that can be replicated in future projects to other cities in the C2SMART consortium and partners. The vision is for a “Network of Living Labs”, which is tentatively dubbed as C2SMART’s “NOLL-Edge” system. Its goal is to be used by city agencies to evaluate emerging technologies and operating policies using a consistent platform so that their effects can be quantified. In the long term, cities may opt to use this test bed as a means of certification for policies and technologies (e.g. NOLL-Edge-certified that policy A can achieve X% welfare improvement in NYC or reduce congestion by Y% for population segments 1, 2, 3, etc.). Based on this overarching goal, the authors set out on these two projects with the following set of objectives: (1) Create an underlying synthetic population for NYC for a recent base year (2016) that includes key emerging modes like Citi Bike and for-hire vehicles (FHVs) like Uber/Lyft/Via; (2) Construct, calibrate, and validate a MATSim model of NYC using the synthetic population; (3) Use the synthetic population and MATSim models to evaluate a set of scenarios for which existing tools are not equipped; and (4) Exploration of other features of MATSim: mobility-on-demand-based autonomous vehicle fleets, bike-share, multimodal travel, and more realistic traffic flow modeling on the links.
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Content Notes:Dataset Access Note: Users who wish access to the dataset must agree to access and re-use terms. See https://doi.org/10.5281/zenodo.4082007 for details.
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