耦合土地利用、交通与建筑能源的协同仿真平台：开发与案例研究
A Co-Simulation Platform Coupling Land Use, Transportation, and Building Energy: Development and Case Study
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中文总结 AI 辅助
该研究开发了集成UrbanSim、POLARIS、CityBES的协同仿真平台，以芝加哥大都市区为例验证其可评估交通与定价政策对土地利用、出行和能源的联合影响。
中文摘要 AI 辅助
土地利用、交通与建筑能源三者相互影响，但城市尺度的研究通常单独对每个部门进行建模。我们提出了一个协同仿真平台，将UrbanSim土地利用模型、基于智能体的交通模型POLARIS以及城市建筑能源模型CityBES耦合为单一集成工作流，其中POLARIS的出行概览数据驱动土地利用，POLARIS智能体活动驱动建筑动态占用。我们以芝加哥大都市区2045年的预测数据为例，在常规情景、高远程办公情景和基于里程的用户收费情景下验证了该平台。两种政策均产生了源于模型反馈而非人为设定的预期方向响应：远程办公使活动向郊区分散，2045年车辆里程减少12.5%；里程收费使活动向城市核心集中，车辆里程减少2.9%。将耦合运行与土地利用固定的非耦合运行对比发现，土地利用反馈在多个县的县级出行效应中贡献超过1个百分点，鉴于里程收费的县级效应仅约3%，该贡献相对于政策效应本身较大，因此仅针对交通的研究会严重低估次区域影响。两种政策均使全市建筑能源提高约1%。这是首个同时集成土地利用、交通与建筑能源的平台，用内生的基于智能体的占用和预测驱动的建筑存量替代预定义的占用时间表和静态建筑存量，使规划者能够评估交通和定价政策对土地利用、出行和能源的联合影响，且其组件模型依赖全国可用数据，只要具备当地建筑存量和校准数据，该方法即可迁移。
英文摘要
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.
