• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.3
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• pp.189-195
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• 2024

K-drone delivery system is a commercial delivery system that ensures compliance with aviation safety. It is equipped with flight routes for automated deliveries and features a drone identification device along with a real-time monitoring system for drone positions. This study proposes the application of an ICAO SMS-based safety management system as an appropriate safety management framework that non-aviation personnel drone operators can adopt. It suggests that applying an ICAO SMS-based safety management system to the K-drone delivery system, similar to Europe and the USA, is valid. To introduce ICAO SMS into the K-drone delivery system, procedures must be established for building a drone safety management system, from business registration to drone operation and training. The main components of the drone safety management system are presented, including 8 items: safety policy and authority and responsibility, risk management, safety assurance, safety promotion, drone control system, drone delivery operation manual, drone maintenance manual, and accident response, incorporating the four fundamental elements of ICAO SMS and European Light UAV operator Certificate standards. Additionally, as a core aspect of the drone safety management system, a seven-step risk assessment procedure is proposed, which includes basic risk identification, hazard identification, risk scenario development, calculation of severity and likelihood, SMS matrix risk assessment, mitigation measures, and implementation determination.

• Journal of Distribution Science
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• v.16 no.2
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• pp.19-24
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• 2018

Purpose - Drone delivery is expected to revolutionize the supply chain industry. This paper aims to introduce a collaborative parcel delivery problem by truck and drone (hereinafter called "TDRP") and propose a novel heuristic method to solve the problem. Research design, data, and methodology - To show the effectiveness of collaborative delivery by truck and drone, we generate a toy problem composed of 9 customers and the speed of drone is assumed to be two times faster than truck. We compared the delivery completion times by 'truck only' case and 'truck and drone' case by solving the optimization problem respectively. Results - We provide literature reviews for truck and drone routing problem for collaborative delivery and propose a novel and original heuristic method to solve the problem with numerical example. By numerical example, collaborative delivery is expected to reduce delivery completion time by 12~33% than 'truck only' case. Conclusions - In this paper, we introduce the TDRP in order for collaborative delivery to be effective and propose a novel and original heuristic method to solve the problem. The results of research will be help to develop effective heuristic solution and optimize the parcel delivery by using drone.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.71-79
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• 2020

Since Amazon announced plans to deliver goods to customers using drones, many countries and companies have become interested in drone logistics delivery services and have begun testing drone delivery for various goods based on service scenarios. Whenever there is news of a successful drone delivery anywhere in the world, people increasingly expect the delivery of goods through drones. Although delivery services using drones are currently in a trial-and-error stage, given technical limitations and institutional and social constraints, a complete shift to drone logistics delivery is not yet possible. In anticipation of the drone logistics delivery service, recent drone delivery tests, current service trends, and requirements for drone delivery service will be examined.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.176-189
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• 2024

Vertical takeoff and landing (VTOL) is a core feature of unmanned aerial vehicles (UAVs), which are commonly referred to as drones. In emerging smart logistics, drones are expected to play an increasingly important role as mobile platforms. Therefore, research on last-mile delivery using drones is on the rise. There is a growing trend toward providing drone delivery services, particularly among retailers that handle small and lightweight items. However, there is still a lack of research on a structural definition of the VTOL drone flight model for multi-point delivery service. This paper describes a VTOL drone flight route structure for a multi-drone delivery service using rotary-wing type VTOL drones. First, we briefly explore the factors to be considered when providing drone delivery services. Second, a VTOL drone flight route model is introduced using the idea of the nested graph. Based on the proposed model, we describe various time-related attributes for delivery services using drones and present corresponding calculation methods. Additionally, as an application of the drone route model and the time attributes, we comprehensively describe a simple example of the multi-drone delivery for first-come-first-served (FCFS) services.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.33-38
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• 2024

In this paper, we propose the implementation of a drone delivery system using artificial intelligence in a situation where the use of drones is rapidly increasing and human errors are occurring. This system requires the implementation of an accurate control algorithm, assuming that last-mile delivery is delivered to the apartment veranda. To recognize the delivery location, a recognition system using the YOLO algorithm was implemented, and a delivery system was installed on the drone to measure the distance to the object and increase the delivery distance to ensure stable delivery even at long distances. As a result of the experiment, it was confirmed that the recognition system recognized the marker with a match rate of more than 60% at a distance of less than 10m while the drone hovered stably. In addition, the drone carrying a 500g package was able to withstand the torque applied as the rail lengthened, extending to 1.5m and then stably placing the package down on the veranda at the end of the rail.

• ETRI Journal
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• v.45 no.5
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• pp.746-757
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• 2023

This study presents a novel safe landing algorithm for urban drone deliveries. The rapid advancement of drone technology has given rise to various delivery services for everyday necessities and emergency relief efforts. However, the reliability of drone delivery technology is still insufficient for application in urban environments. The proposed approach uses the "landing angle control" method to allow the drone to land vertically and a rapidly exploring random tree-based collision avoidance algorithm to generate safe and efficient vertical landing paths for drones while avoiding common urban obstacles like trees, street lights, utility poles, and wires; these methods allow for precise and reliable urban drone delivery. We verified the approach within a Gazebo simulation operated through ROS using a six-degree-of-freedom drone model and sensors with similar specifications to actual models. The performance of the algorithms was tested in various scenarios by comparing it with that of stateof-the-art 3D path planning algorithms.

• Journal of Auto-vehicle Safety Association
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• v.16 no.2
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• pp.20-26
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• 2024

The delivery using drones has been attracting attention because it can innovatively reduce the delivery time from the time of order to completion of delivery compared to the current delivery system, and there have been pilot projects conducted for safe drone delivery. However, the current drone delivery system has the disadvantage of limiting the operational efficiency offered by fully autonomous delivery drones in that drones mainly deliver goods to pre-set landing sites or delivery bases, and the final delivery is still made by humans. In this paper, to overcome these limitations, we propose obstacle detection and landing site selection algorithm based on a vision sensor that enables safe drone landing at the delivery location of the product orderer, and experimentally prove the possibility of station-to-door delivery. The proposed algorithm forms a 3D map of point cloud based on simultaneous localization and mapping (SLAM) technology and presents a grid segmentation technique, allowing drones to stably find a landing site even in places without prior information. We aims to verify the performance of the proposed algorithm through streaming data received from the drone.

• Electronics and Telecommunications Trends
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• v.33 no.4
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• pp.70-80
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• 2018

Drones are now widely used in civilian applications such as filming, leisure, agricultural control, monitoring, and the generation of 3D-spatial information, deviating only from military drones. In the field of logistics, prototypes are emerging in the area of logistics transportation, and to develop a future transportation service under the name of a drone tax, each country is introducing its first flight results using its own unique drones. In this paper, we review the domestic and overseas trends of drone delivery service technology, which requires various capabilities such as automatic flight, and review the related core technologies. We then propose the flight capability and road map of a drone delivery service according to the detailed conditions such as the flight area, visibility, and flight method. Additionally, in connection with the postal processing of the Korea Post Office, which would be a main demand for this type of service, we describe a method for realizing a drone delivery service based on the structure, scenario, and deployment of the drone delivery system.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.175-184
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• 2022

This study investigates the impact of COVID-19 anxiety on dietary lifestyle and the effect of different dietary lifestyle on the intention to use drone food delivery services. A questionnaire survey was conducted among 356 Chinese consumers aware of drone food delivery services. Results show that First, COVID-19 anxiety significantly impacted dietary lifestyle, including health pursuit, safety pursuit, and convenience pursuit. Second, the dietary lifestyle of health pursuit, fashion pursuit, and convenience pursuit positively affected service perceptions, including perceived safety and perceived rapidity, perceived compatibility. The dietary lifestyle of taste pursuit positively associated with safety of drone food delivery service, while the dietary lifestyle of safety pursuit positively related to safety and rapidity of drone food delivery services. Third, the perceptions related to security, rapidity, and compatibility of drone food delivery services enhanced service usage intention. Results show that COVID-19 anxiety was positively associated with dietary lifestyle, influencing consumer attitudes toward drone food delivery services.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.53-64
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• 2019

The purpose of this study is to find out the fast delivery route that several drones return a truck again after departing from it for delivery locations at each cluster while the truck goes through the cluster composed of several delivery locations. The main issue is to reduce the total delivery time composed of the delivery time by relatively slow trucks via clusters and the sum of maximum delivery times by relatively fast drones in each cluster. To solve this problem, we use a three-step heuristic approach. First, we cluster the nearby delivery locations with minimal number of clusters satisfying a constraint of drone flight distance to set delivery paths for drones in each cluster. Second, we set an optimal delivery route for a truck through centers of the clusters using the TSP model. Finally, we find out the moved centers of clusters while maintaining the delivery paths for the truck and drones and satisfying the constraint of drone flight. distance in the two-dimensional region to reduce the total delivery time. In order to analyze the effect of this study model according to the change of the number of delivery locations, we developed a R-based simulation prototype and compared the relative efficiency, and performed paired t-test between TSP model and the cluster-based models. This study showed its excellence through this experimentation.