Dynamic Traffic Assignment vs. Frank-Wolfe Route Assignment Impacts on Emissions and Energy Inventories
| 项目名称： | Dynamic Traffic Assignment vs. Frank-Wolfe Route Assignment Impacts on Emissions and Energy Inventories |
| 摘要： | The Frank-Wolfe algorithm is a common static traffic assignment (STA) solution used in travel demand models. Frank-Wolfe algorithms are capable of finding efficient solutions at a large scale due to their efficient computational nature. However, STA algorithms are generally criticized for: (1) their failure to address complex traffic flow phenomena, such as the formation and propagation of queues affecting corridor travel time; (2) only indirectly accounting for the impacts of corridor-level traffic control systems; and (3) the assumption that the least-cost path selection is based on a uniform cost function which applies to all users (irrespective of trip purpose, demographics, employment type, etc.). Dynamic traffic assignment (DTA) models are designed to resolve the problems identified above, but they require much greater computational resources, calibration efforts, and preparation of high-resolution data. In this research, the team will implement the Frank-Wolfe algorithm and DTA with the same travel demand model input data to generate two sets of travel paths. The team will comparatively assess the energy use and emissions impacts of these two distinctly different traffic assignment algorithms and their resulting travel paths sets by applying MOVES-Matrix (to generate exact same output with MOVES). |
| 状态： | Active |
| 资金： | 120000 |
| 资助组织： | National Center for Sustainable Transportation<==>Office of the Assistant Secretary for Research and Technology<==>Georgia State Road and Tollway Authority |
| 项目负责人： | Iacobucci, Lauren |
| 执行机构： | National Center for Sustainable Transportation<==>Georgia Institute of Technology, Atlanta |
| 开始时间： | 20201001 |
| 预计完成日期： | 20210930 |
| 主题领域： | Environment；Highways；Operations and Traffic Management；Planning and Forecasting |
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