Advanced Behavioral Analysis of High Resolution Mobility Data
| 项目名称： | Advanced Behavioral Analysis of High Resolution Mobility Data |
| 摘要： | Activity-based models (ABMs) are now well established as the state-of-art in modeling travel demand and supporting decision-making. One challenge to ABMs is their need for detailed, high resolution activity data. Recent developments in smartphone-based travel surveys have helped overcome this challenge, but these new data complicate the modelling. Identifying the correct model structure and specification is difficult. Inter- and intra-person heterogeneity exists also across choice dimensions and the boundaries between primary and non-primary activities is becoming more blurry. This project explores a data-driven non-parametric approach for daily activity pattern generation without behavioral assumptions: Variational Auto-encoder (VAE). This research aims to make four contributions to transportation modeling: deriving realistic activity patterns that resemble the level of heterogeneity in real data; providing an interpretable & explorative tool; allowing for rapid model development and estimation; and being useful for forecasting & policy analysis. In the end, the research team aims to facilitate ABM modeling, making the models more richly reflect real-world conditions while also making them more computationally tractable and, ultimately, more easily operationalized in forecasting and planning practice. |
| 状态： | Active |
| 资金： | 100000 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 管理组织： | New England University Transportation Center |
| 项目负责人： | Coughlin, Joseph F |
| 执行机构： | Massachusetts Institute of Technology, Cambridge |
| 主要研究人员： | Zegras, Christopher |
| 开始时间： | 20180901 |
| 预计完成日期： | 20190630 |
| 实际结束时间： | 0 |
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