News • 29.06.2020

Could drones deliver packages more efficiently by hopping on the bus?

Aerial transport could take load off city streets – provided drones a ride

A white drone flying high in a city with skyscrapers...
Source: PantherMedia/leolintang

One-click purchases and instant delivery have helped fuel the growth of e-commerce, but this convenience has come at the cost of increased traffic congestion, longer commute times, and strained urban communities. A 2018 report from Texas A&M University found that delivery trucks represent just 7 percent of U.S. traffic but account for 28 percent of the nation's congestion. Delivery drones could help take some of the load off the pavement, and aerial delivery systems already operate in some countries. But even the best drones have limited payload capacity and flight range. What if we could combine the last-mile flexibility of drones with the long-haul capacity of ground-based vehicles to make e-commerce more traffic-friendly?

In a recent presentation at the IEEE International Conference on Robotics and Automation (ICRA), our Stanford research team unveiled a framework for routing a large fleet of delivery drones over ground transit networks. In our setup, the drones were able to hitch rides on public transit vehicles to save energy and increase flight range. Our algorithm decided which drones should make which deliveries, one package at a time, in what order – and when to fly versus hitching a ride.

In our experiments, we ran simulations over two real-world public bus networks and corresponding delivery areas in San Francisco (150 square kilometers) and the Washington, D.C., Metropolitan Area (400 square kilometers). We found that the drones could quadruple their effective flight range by strategically hitching rides on transit vehicles. We also found that the "makespan" of any batch of deliveries – the longest it took for any drone in the team to deliver one of the packages in the batch – was under an hour for San Francisco and under two hours for the Washington, D.C., area.

The framework was created by the Stanford Intelligent Systems Laboratory, led by Mykel Kochenderfer, and the Autonomous Systems Laboratory, led by Marco Pavone. "Delivery drones are the future," Kochenderfer said. "By using ground transit judiciously, drones have the potential to provide safe, clean and cost-effective transport."

Source: Stanford School of Engineering

related articles:

popular articles:

Thumbnail-Photo: REMIRA survey: companies not fully able to deliver during stocktaking...
26.10.2023   #brick and mortar retail #retail

REMIRA survey: companies not fully able to deliver during stocktaking

One in four companies is unable to deliver and produce during legally required inventory.

Despite of this, only 10% of companies have taken advantage of the possibility of quick and easy sample stocktaking using statistical methods. This is the result of a representative Civey survey among German employees who make decisions regarding ...

Thumbnail-Photo: REMIRA case report: greater transparency and more efficient processes...
31.10.2023   #brick and mortar retail #retail

REMIRA case report: greater transparency and more efficient processes

DURAL enhances inventory management worldwide with LOGOMATE

Optimised warehouse stocks, improved product availability and a significant reduction in time-consuming tasks for employees have all been achieved thanks to the introduction of the LOGOMATE inventory management software at DURAL. After successfully ...

Thumbnail-Photo: Retail Logistics: The 10 most important trends and forecasts...
04.12.2023   #data analysis #artificial intelligence

Retail Logistics: The 10 most important trends and forecasts

What you can prepare for as a retailer

Producers, manufacturers and consumers are connected through distribution. However, in a fast-paced world with rapid technological progress, it is precisely this link that is under increasing pressure. It's no secret that the industry will ...

Supplier

REMIRA Group GmbH
REMIRA Group GmbH
Phoenixplatz 2
44263 Dortmund