AI summaryⓘ
The authors created a new computer platform that links land use, transportation, and building energy models so they work together instead of separately. They tested it using future scenarios for Chicago and found that policies like telecommuting and mileage fees changed travel patterns and building energy use in ways that the model itself predicted, not just assumed. For example, telecommuting moved activities to suburbs and cut driving more than mileage fees, while mileage fees pushed people back to the urban core. They also showed that ignoring land use changes can lead to wrong conclusions about travel impacts. This platform helps planners see how transportation policies affect land use, travel, and energy all at once.
land usetransportation modelingbuilding energy modelco-simulationagent-based modelurban planningtelecommutingmileage-based user feetravel demandbuilding occupancy
Authors
Gopindra Sivakumar Nair, Yilin Jiang, Samuel Maurer, James Cook, Nazmul Arefin Khan, Joshua A. Auld, Tianzhen Hong, Arezoo Besharati, Paul Waddell
Abstract
Land use, transportation, and building energy shape one another, yet urban-scale studies typically model each sector in isolation. We present a co-simulation platform that couples the UrbanSim land-use model, the POLARIS agent-based transportation model, and the CityBES urban building energy model into a single integrated workflow, with POLARIS travel skims driving land use and POLARIS agent activities driving dynamic building occupancy. We demonstrate the platform with forecasts through 2045 for the Chicago metropolitan area under a business-as-usual case, a high-telecommuting scenario, and a mileage-based user fee scenario. Both policies produced expected-direction responses that emerged from the model feedbacks rather than being imposed. Telecommuting decentralized activity toward outlying areas and cut 2045 vehicle miles traveled by 12.5%, whereas the mileage fee recentralized activity toward the urban core and cut it by 2.9%. Comparing coupled runs against uncoupled runs that hold land use fixed shows that the land-use feedback contributes over one percentage point to the county-level travel effect in several counties, large relative to the policy effect itself since the mileage fee's county-level effects are only about three percent, so a transportation-only study would materially misstate the sub-regional impact. Both policies raised citywide building energy by about 1%. This is the first platform to integrate land use, transportation, and building energy simultaneously, replacing predefined occupancy schedules and static building stocks with endogenous agent-based occupancy and a forecast-driven building stock. It lets planners evaluate transportation and pricing policies for their joint land use, travel, and energy consequences, and its component models rely on nationally available data, making the approach transferable given local building-stock and calibration data.