United States Department of Transportation
i
Dynamic Origin-Destination Estimation (DODE) under Incidents Using Individual Trajectories Data [supporting dataset]
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2023-12-11
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[JSON-3.16 KB]
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Abstract:This project develops a model that encapsulates travelers’ route choice behavior under unplanned incidents. Travel behavior in terms of route choices under incidents is modeled based on a disutility function for individuals and the calibrated regional network model. This novel behavioral model can be further integrated into a process of Dynamic Origin-Destination Estimation (DODE) that calibrates dynamic network simulation under incidents. In an of-line manner, we intend to GPS-based traces data to learn the disutility function of individuals’ travel choice under incidents. When deployed in real-time, those initial disutility functions can be seen as the expected route choices of individual travelers under incidents, which can be further tuned and refined in real time provided with real-time data. Furthermore, the real-time simulation and DODE receive real-time traffic data feeds (INRIX or GPS traces) and calibrate the en-route route choices in the real time, corrects the forecast of incident-induced traffic congestion in the next hour, and computes the optimal traffic diversion ratios for pre-determined detour routes. Those research steps are left for future work. However, the first step is developing models for route choices under unplanned incidents and algorithms to learn those choices from data.
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Content Notes:To access this dataset, please visit the project's GitHub page at: https://github.com/HaochengDuan/Incident_Route_Choice
National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT’s Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. The current level of dataset documentation is the responsibility of the dataset creator. NTL staff last accessed this dataset at its repository URL on 2024-03-04. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDataCurator@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
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