  Multi-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 multi-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 use SUMO
simulations and derive a mathematical latency function for 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.
