Papers › Modeling 100% Electrified Transportation in NYC
Modeling 100% Electrified Transportation in NYC
Jingrong Zhang, Amber Jiang, Brian Newborn, Sara Kou, Robert Mieth
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
Envisioning a future 100% electrified transportation sector, this paper uses socio-economic, demographic, and geographic data to assess electric energy demand from commuter traffic. We explore the individual mode choices, which allows to create mode-mix scenarios for the entire population, and quantify the electric energy demand for each scenario using technical specifications of battery and electric drives technology in combination with different charging scenarios. Using data sets for New York City, our results highlight the need for infrastructure investments, the usefulness of flexible charging policies, and the positive impact of incentivizing micromobility and mass-transit options. Our model and results are publicly available as interactive dashboard.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections