United States Department of Transportation
i
Dynamic Origin-Destination Estimation (DODE) under Incidents Using Individual Trajectories Data
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2023-09-01
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[PDF-2.14 MB]
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Edition:Final Report
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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 develop models for route choices under unplanned incidents and algorithms to learn those choices from data.
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