Congestion-aware Bi-modal Delivery Systems Utilizing Drones
Congestion-aware Bi-modal Delivery Systems Utilizing Drones
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DOI：
10.23919/ecc55457.2022.9838052
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发表时间：
2021-04
期刊：
影响因子：
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通讯作者：
M. Beliaev;Negar Mehr;Ramtin Pedarsani
中科院分区：
文献类型：
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作者：
M. Beliaev;Negar Mehr;Ramtin Pedarsani
双模式交付系统是解决日益增长的电子商务需求所带来的挑战的一个有前途的解决方案。由于无人机对物流网络（如配送系统）的潜在好处，一些国家已采取措施将无人机纳入其空域。在本文中，我们的目标是通过开发一个由卡车和无人机组成的双模运输系统的数学模型来量化这种潜力。我们提出了一个优化配方，可以有效地解决，以设计社会最优的路由和分配政策。我们将社会成本的道路拥堵和包裹交付延迟在我们的配方。我们的模型能够量化无人机对缓解道路拥堵的影响，并可以解决最小化所选目标所需的路径路由。为了准确地捕捉停止卡车对道路延迟的影响，我们通过模拟卡车和汽车共享的道路，使用SUMO对其进行建模。在此基础上，我们表明，所提出的框架是计算上可行的规模，由于其依赖于凸二次优化技术。
Bi-modal delivery systems are a promising solution to the challenges posed by the increasing demand of e-commerce. Due to the potential benefit drones can have on logistics networks such as delivery systems, some countries have taken steps towards integrating drones into their airspace. In this paper we aim to quantify this potential by developing a mathematical model for a Bi-modal delivery system composed of trucks and drones. We propose an optimization formulation that can be efficiently solved in order to design socially-optimal routing and allocation policies. We incorporate both societal cost in terms of road congestion and parcel delivery latency in our formulation. Our model is able to quantify the effect drones have on mitigating road congestion, and can solve for the path routing needed to minimize the chosen objective. To accurately capture the effect of stopping trucks on road latency, we model it using SUMO by simulating roads shared by trucks and cars. Based on this, we show that the proposed framework is computationally feasible to scale due to its reliance on convex quadratic optimization techniques.