Sizing of the Drone Delivery Fleet Considering Energy Autonomy

Comparison of exact and approximate approaches to UAVs mission contingency planning in dynamic environments

This paper presents a novel approach to the joint proactive and reactive planning of deliveries by an unmanned aerial vehicle (UAV) fleet. We develop a receding horizon-based approach to contingency planning for the UAV fleet's mission. We considered the delivery of goods to spatially dispersed customers, over an assumed time horizon. In order to take into account forecasted weather changes that affect the energy consumption of UAVs and limit their range, we propose a set of reaction rules that can be encountered during delivery in a highly dynamic and unpredictable environment. These rules are used in the course of designing the contingency plans related to the need to implement an emergency return of the UAV to the base or handling of ad hoc ordered deliveries. Due to the nonlinearity of the environment's characteristics, both constraint programming and genetic algorithm paradigms have been implemented. Because of the NP-difficult nature of the considered planning problem, conditions have been developed that allow for the acceleration of calculations. The multiple computer experiments carried out allow for comparison representatives of the approximate and exact methods so as to judge which approach is faster for which size of the selected instance of the UAV mission planning problem.

The Use of Drones for Last-Mile Delivery: A Numerical Case Study in Milan, Italy

The increasing use of e-commerce introduces major challenges for last-mile delivery, which is critical to ensure smooth functioning of supply chains. Besides the speed and cost of delivery, which are the most important factors for last-mile logistics, environmental and social sustainability factors are taking on an increasingly important role, especially in urban areas. In this perspective, last-mile delivery by drones could be a good choice both in terms of transport speed and sustainability. Being electrically powered, drones can reduce environmental impact; moreover, they enable the reduction of road congestion since they do not interfere with land infrastructures. The goal of this study is to analyse the viability of drones for last-mile delivery in the Italian city of Milan. A stated preference survey was carried out to assess end-user propensity towards drones. Using these results, a goods delivery service by drones was designed. Furthermore, a preliminary financial analysis was performed to evaluate the benefits for a company that would provide such a transport service. Findings show that last-mile delivery by drones can be successfully used to deliver small and light packages, reducing environmental and social impacts, and ensuring profits for the transport provider.

A Literature Review of Drone-Based Package Delivery Logistics Systems and Their Implementation Feasibility

In recent years, e-commerce businesses have seen an increase in the daily volume of packages to be delivered, as well as an increase in the number of particularly demanding customer expectations. In this respect, the delivery mechanism became prohibitively expensive, particularly for the final kilometer. To stay competitive and meet the increased demand, businesses began to look for innovative autonomous delivery options for the last mile, such as autonomous unmanned aerial vehicles/drones, which are a promising alternative for the logistics industry. Following the success of drones in surveillance and remote sensing, drone delivery systems have begun to emerge as a new solution to reduce delivery costs and delivery time. In the coming years, autonomous drone sharing systems will be an unavoidable logistical solution, especially with the new laws/recommendations introduced by the Flight World Organization on how to organize the operations of these special unmanned airline systems. This paper provides a comprehensive literature survey on a set of relevant research issues and highlights the representative solutions and concepts that have been proposed thus far in the design and modeling of the logistics of drone delivery systems, with the purpose of discussing the respective performance levels reached by the various suggested approaches. Furthermore, the paper also investigates the central problems to be addressed and briefly discusses and outlines a series of interesting new research avenues of relevance for drone-based package delivery systems.

In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery

We autonomously directed a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or "drone" to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, were varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.

Reactive UAV Fleet’s Mission Planning in Highly Dynamic and Unpredictable Environments

Unmanned aerial vehicles (UAVs) create an interesting alternative for establishing more sustainable urban freight deliveries. The substitution of traditional trucks in the last-mile distribution by a UAV fleet can contribute to urban sustainability by reducing air pollution and increasing urban freight efficiency. This paper presents a novel approach to the joint proactive and reactive planning of deliveries by a UAV fleet. We develop a receding horizon-based approach to reactive, online planning for the UAV fleet’s mission. We considered the delivery of goods to spatially dispersed customers over an assumed time horizon. Forecasted weather changes affect the energy consumption of UAVs and limit their range. Therefore, consideration should be given to plans for follow-up tasks, previously unmet needs, and predictions of disturbances over a moving time horizon. We propose a set of reaction rules that can be encountered during delivery in a highly dynamic and unpredictable environment. We implement a constraint programming paradigm, which is well suited to cope with the nonlinearity of the system’s characteristics. The proposed approach to online reactive UAV routing is evaluated in several instances. The computational experiments have shown that the developed model is capable of providing feasible plans for a UAV fleet’s mission that are robust to changes in weather and customer’s orders.

The Adoption of Green Vehicles in Last Mile Logistics: A Systematic Review

Widespread adoption of green vehicles in urban logistics may contribute to the alleviation of problems such as environmental pollution, global warming, and oil dependency. However, the current adoption of green vehicles in the last mile logistics is relatively low despite many actions taken by public authorities to overcome the negative externalities of distributing goods in cities. This paper presents a comprehensive literature review on studies investigating the adoption of green vehicles in urban freight transportation, paying specific attention to e-commerce. To shed light on the adoption of green vehicles in city logistics, the paper conducts a systematic review of the empirical literature on the topic. The 159 articles reviewed were classified into the following: (a) Optimization and scheduling (67 papers); (b) policy (55 papers); (c) sustainability (37 papers). Among the 159 articles, a further selection of 17 papers dealing with e-commerce, i.e., studies that highlight the most relevant aspects related to the integration of green vehicles in e-commerce urban logistics, was performed. Our findings indicate that green vehicles are competitive in urban deliveries characterized by frequent stop-and-go movements and low consolidation levels while incentives are still necessary for their adoption. The use of autonomous vehicles results the most promising and challenging solution for last-mile logistics.

Mathematical Investigation on the Sustainability of UAV Logistics

Unmanned aerial vehicles (UAVs) are expected to make groundbreaking changes in the logistics industry. Leading logistics companies have been developing and testing their usage of UAVs recently as an environmentally friendly and cost-effective option. In this paper, we investigate how much the UAV delivery service is environmentally friendly compared to the traditional ground vehicle (GV) delivery service. Since there are fuel (battery) and loadable weight restrictions in the UAV delivery, multi-hopping of UAV is necessary, which may cause a large consumption of electrical energy. We present a two-phase approach. In Phase I, a new vehicle routing model to obtain optimal delivery schedules for both UAV-alone and GV-alone delivery systems is proposed, which considers each system’s restrictions, such as the max loadable weight and fuel replenishment. In Phase II, CO2 emissions are computed as a sustainability measure based on the travelling distance of the optimal route obtained from Phase I, along with various GV travel-speeds. A case study finds that the UAV-alone delivery system is much more CO2 efficient in all ranges of the GV speeds investigated.

A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles

The use of Unmanned Aerial Vehicles (UAVs) is rapidly growing in popularity. Initially introduced for military purposes, over the past few years, UAVs and related technologies have successfully transitioned to a whole new range of civilian applications such as delivery, logistics, surveillance, entertainment, and so forth. They have opened new possibilities such as allowing operation in otherwise difficult or hazardous areas, for instance. For all applications, one foremost concern is the selection of the paths and trajectories of UAVs, and at the same time, UAVs control comes with many challenges, as they have limited energy, limited load capacity and are vulnerable to difficult weather conditions. Generally, efficiently operating a drone can be mathematically formalized as a path optimization problem under some constraints. This shares some commonalities with similar problems that have been extensively studied in the context of urban vehicles and it is only natural that the recent literature has extended the latter to fit aerial vehicle constraints. The knowledge of such problems, their formulation, the resolution methods proposed—through the variants induced specifically by UAVs features—are of interest for practitioners for any UAV application. Hence, in this study, we propose a review of existing literature devoted to such UAV path optimization problems, focusing specifically on the sub-class of problems that consider the mobility on a macroscopic scale. These are related to the two existing general classic ones—the Traveling Salesman Problem and the Vehicle Routing Problem. We analyze the recent literature that adapted the problems to the UAV context, provide an extensive classification and taxonomy of their problems and their formulation and also give a synthetic overview of the resolution techniques, performance metrics and obtained numerical results.