An Optimization Framework for Dynamic Population Evacuation Problem Using a Vehicular Ad Hoc Network for Emergency Communication
Résumé
This study proposed a new framework to solve dynamic population evacuation (DPE) problems, considering the planning phase and vehicular communication during the online evacuation management phase. In the planning phase, an initial evacuation plan is obtained by dynamically solving the shelter allocation problem for destination choice and dynamic traffic assignment (DTA) for path choice towards the chosen destinations. The DPE process then starts with the initial plan, and thanks to vehicular ad hoc network (VANET), evacuees communicate during the evacuation. We use VANET under the vehicular cloud computing (VCC) architecture to update vehicle decisions chosen by the initial plan, considering the dynamic evolution of the hazard and traffic congestion levels. To validate the proposed framework, we apply it to a real test case of Luxembourg city. We compare the proposed solution with existing planning methods in the literature. Results show that online solving of DPE can minimize mean evacuation time and network clearance time by more than 10% compared to other models with the only initial plan. In other words, updating evacuation guidance messages during the DPE process leads us to a more effective evacuation process. In addition, we analyze the performance of the proposed framework by changing the penetration rate of connected vehicles in VANET, and we observe that by increasing the penetration rate, the clearance time decreases.
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