'Home delivery drone system that expands the range that can be delivered by saving electricity on the bus' is being developed
In recent years, the use of drones has been sought as a home delivery method that replaces conventional systems.In Australia,
[1909.11840] Efficient Large-Scale Multi-Drone Delivery Using Transit Networks
https://arxiv.org/abs/1909.11840
Stanford lab envisions delivery drones that save energy by taking the bus | VentureBeat
https://venturebeat.com/2020/06/03/stanford-lab-envisions-delivery-drones-that-save-energy-by-taking-the-bus/
Although some home delivery drones have been introduced so far, most deliveries are available only in the suburbs. This is because commercial drones are not allowed to fly in urban areas due to dynamic urban environments and the presence of many unexpected obstacles.
However, the research team of Stanford Intelligent Systems Laboratory (SISL) and Autonomous Systems Lab at Stanford University has developed an algorithm that expands the possibility of home delivery drones by using buses that run in urban areas. “Our approach seeks to minimize the time it takes to complete any courier.” “Combining the advantages of public transport and drones not only makes a huge commercial profit, but also has a social impact. Can be given,' says the research team.
The approach adopted by the research team is that a drone loaded with luggage flies away from the distribution center, flies from the distribution center to a bus running nearby, 'rides' it, and when it approaches the vicinity of the delivery destination, it again flies from the bus and delivers it. What to do. Also, it is said that the drone does not only board one bus, but there are also cases where 'transfer' to another bus.
In order to ensure smooth operation of this public transportation and unmanned drone approach, it is necessary to put together an appropriate schedule that includes available drones, delivery destinations of individual packages, and bus schedules. Therefore, the research team combined the information of 'drone', 'delivery destination of baggage' 'delivery center where drone waits and returns' 'bus that travels on fixed route', and builds AI algorithm to build optimal boarding and delivery schedule Developed.
The algorithm developed by the research team seems to be able to handle cases where up to 200 drones deliver 5000 packages. When we actually conducted a simulation using the transportation systems of the
In this study, experiments were not actually conducted in urban areas, and problems such as delays due to traffic conditions and obstacles were not fully considered. ``The key directions for the future are to estimate the impact of operating our framework on cost and road congestion, and identify potential external impacts such as noise pollution and impacts on urban communities,'' the team said. Is to do a case study.'
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