Reducing Risks by Transporting Dangerous Cargo in Drones

Abstract

The transportation of dangerous goods by truck or railway multiplies the risk of harm to people and the environment when accidents occur. Many manufacturers are developing autonomous drones that can fly heavy cargo and safely integrate into the national air space. Those developments present an opportunity to not only diminish risk but also to decrease cost and ground traffic congestion by moving certain types of dangerous cargo by air. This work identified a minimal set of metropolitan areas where initial cargo drone deployments would be the most impactful in demonstrating the safety, efficiency, and environmental benefits of this technology. The contribution is a new hybrid data mining workflow that combines unsupervised machine learning (UML) and geospatial information system (GIS) techniques to inform managerial or investment decision making. The data mining and UML techniques transformed comprehensive origin–destination records of more than 40 commodity category movements to identify a minimal set of metropolitan statistical areas (MSAs) with the greatest demand for transporting dangerous goods. The GIS part of the workflow determined the geodesic distances between and within all pairwise combinations of MSAs in the continental United States. The case study of applying the workflow to a commodity category of dangerous goods revealed that cargo drone deployments in only nine MSAs in four U.S. states can transport 38% of those commodities within 400 miles. The analysis concludes that future cargo drone technology has the potential to replace the equivalent of 4.7 million North American semitrailer trucks that currently move dangerous cargo through populated communities.

Risks of Drone Use in Light of Literature Studies

“…The use of UAVs to transport materials is marked by advantages such as reduced costs, increased safety, and increased efficiency [ 166 , 174 , 176 ]; however, not everything can be transported this way. Researchers are exploring the possibilities of using UAVs for transportation while noting their limitations.…”

Data-Driven Deployment of Cargo Drones: A U.S. Case Study Identifying Key Markets and Routes

“…Electrified autonomous aircraft (EAA) play a crucial role in urban air mobility (UAM) and regional air mobility (RAM) initiatives, providing "last mile" and "middle mile" transport services, respectively [1]. Environmental stewardship and sustainability also contribute to EAA utilization, as they can help reduce the adverse effects of traffic congestion [10] and protect the environment from dangerous cargo spills [11]. However, commercial EAA services face uncertainties due to current federal regulations restricting their use [12].…”