Toward Efficient Urban Emergency Response Using UAVs Riding Crowdsourced Buses

Unmanned Aerial Vehicles (UAVs) are widely applied in smart city applications such as urban sensing and delivery, due to the UAVs' agility, low cost and not being restricted by ground road conditions. However, the limited battery capacity becomes one of the biggest obstacles to the application of UAVs. To address this issue, this paper investigates an emergency response application, in which UAVs generally ride crowdsourced buses to save energy and respond to a stochastic emergency event (such as a traffic accident) when the event occurs. For the bus-based UAV response paradigm, a single UAV response process with the constraint of the bus mobility is first modeled. Subsequently, a data-driven UAV path planning algorithm is designed. Then two emergency response cases by multi-UAV are investigated. One case is irregular emergency response, whose objective is to maximize the temporal-spatial coverage of the urban area. The other case is predictable emergency response, which optimizes the response performance to these emergencies. Thereafter, the bus-stimulating problems for the two cases are formulated and solved. Finally, utilizing a real-world bus trajectory dataset generated by a large-scale bus fleet and a traffic event dataset, the emergency response performance of the bus-based UAV response paradigm is comprehensively evaluated. The results show that (1) with only 30 UAVs, 90% of Shenzhen city can be covered in the irregular emergency response case; (2) with only 50 UAVs, the average response delay to the emergencies is shorter than 1.5 minutes, which is 56% shorter than baselines, in the predictable emergencies response case.