Whenever time is critical, drones are the best delivery option: Guest blog by VVA Brussel

As mobility is evolving at a rapid pace, taking transport above and beyond the roads and into the 3^rd dimension is very much expected. Use cases such as transporting biomedical material, last mile deliveries and traffic management by unmanned cost efficient vehicles that do not get stuck in traffic, such as drones, are already being tackled in projects run by ERTICO Partners. The public and private sectors within the ERTICO Partnership see how drones form an integral part of urban mobility and wish to come around the table and discuss the ‘how’. 

ERTICO Partner VVA Brussels explored new, more ‘ecological’ and more efficient means of delivery such as drones. The Brussels based consultancy company developed a cost assessment model to analyse different business cases for using drones in delivery  in the framework of the EGNSS4RPAS project funded by the European Commission. Are drones the best option in comparison to other ‘ecological’ vehicles such as electric bikes and electric vans? Will drones replace traditional delivery methods or create new niche business opportunities? Find out below.

When time is critical, delivering biomedical samples with drones is best

In the healthcare sector, time is vital and can save times. That is why the transport of biomedical and specimens’ samples between hospitals or laboratories needs to be done as fast and timely as possible. Currently, most hospitals and laboratories use traditional courier services which means that despite the small size and weight of each sample, they typically need to wait for a minimum volume before dispatching them. Moreover, what can further delay the process is that delivery time is not always constant as it depends on traffic conditions. In this context, drones come as a good solution because of their ability to provide faster, cheaper and more reliable delivery services.

The cost assessment analysis undertaken by VVA compared the cost-effectiveness of drones* in relation to electric vans for the delivery of biomedical samples. The case study analysed the transport of samples in the city of Rouen (France) between three hospitals located in three different areas of the city sending samples to the central hospital that has the necessary equipment to carry out the analysis of the samples and provide diagnostics. Based on discussions with stakeholders, it is estimated that 11 deliveries per day are undertaken between these hospitals and the average distance between sites is approximately 6.3 km. Although each sample package weights less than 2 kg, as the delivery are currently done by 5 utility vehicles, each delivery package currently combines samples up to a maximum weight of 30 kg per delivery to reduce the number of required delivery trips.

For the future scenario, the analysis considered the replacement of the current vehicles by either electric vans or drones. For the drone scenario, fixed routes between the different hospitals, possibly from rooftop to rooftop, are considered. This would mean that most of the operation would be performed under open sky, what would also make the flight approval process less complex.

The outcomes of the analysis indicate that the delivery of biomedical samples with drones would take approximately 15 min, almost a third of 42 min estimated for e-vans. In addition, the delivery by drones is also expected to be 60% cheaper. The cost per delivery by drones is estimated at EUR 1.92 while delivery with e-van would cost EUR 4.59. The analysis also concluded that EGNOS solution is the preferred option to support drone navigation not only because of the higher position accuracy in comparison to GPS but mainly because it provides timely warnings to users when the system should not be used for navigation (so-called system integrity), feature that is critical for operations in urban areas where the risk over people on ground is higher.

The conclusion is that in time-critical operations (less than 60 min), the higher speed and reliability of delivery of biomedical samples are essential. Therefore, the higher cost-effectiveness makes the delivery by drones advantageous. It would also make the delivery more reliable and independent of the traffic conditions in the city. On the other hand, when time is not as critical (for example, if the delivery could take more than 2 hours), the larger volume of the e-van would make it more cost-effective than drones.

Why equipping drones with European satellite navigation makes sense

Drones currently rely on multiple sensors for their navigation, positioning and obstacle avoidance. Lidar and infrared sensors are commonly used to support navigation and obstacle avoidance functions. For absolute positioning, GPS is still the main solution used but European Satellite Navigation solutions –EGNOS and Galileo- are becoming mass-market and gaining terrain in the drones’ segment. Moreover, in the near future, Galileo will deliver unmatched services like OSNMA (Open Service Navigation Message Authentication), which will enhance protection against certain cyberattacks, and High Accuracy Service, with position accuracies down to 20 cm.

Within the EGNSS4RPAS project, field trials were undertaken in segregated airspace and urban areas by the consortium partners, GMV and CATEC, to compare the performance of GPS-only solutions with solutions including Galileo and EGNOS.

The trial results indicate that the use of Galileo in dual constellation (GPS+Gal) significantly improves GPS-only performance in terms of accuracy, availability and continuity. EGNOS, being an augmentation system, not only enhances the position accuracy of GPS down to sub-meter level, but also can provide timely warnings to users when the system should not be used for navigation (so-called system integrity).

Table 1: Position error results from trials for open sky operations – Multicopter and GNSS single-frequency

Table 1 presents the results of the trials undertaken to simulate open sky operations with drones. The horizontal position accuracy achieved by the EGNOS solution was 60% more accurate than GPS-only, reaching less than 40 cm. For the vertical accuracy, EGNOS achieved accuracy below 50 cm, which is a great improvement if compared to the 3.4 m accuracy achieved by GPS-only.

The horizontal and vertical position error deriving from the trial results were converted into a distance adjustment factor that was used to simulate the trajectory undertaken by the drone in comparison to the most direct trajectory (position error = zero).  Under normal conditions with open sky without disruptions, it is estimated that EGNOS would be able to ensure that the most direct trajectory is followed while the GPS-alone solutions would have an error of 1%. However, when the visibility of satellites could be blocked by certain obstacles, such as urban areas with high rising buildings, the error of GPS-only solutions could almost reach 40% while EGNOS could remain with an error at only 1%. In addition, as EGNOS’ integrity messages enhance the overall safety of the operations, it is expected that insurance primes charged to drone operations could be lower due to the lower risks involved. The cost assessment considered a 5% reduction, conservatively.

It is important to highlight that as EGNOS and Galileo are already mass-market in several sectors, they are provided by the main receiver manufacturers, such uBlox, at no additional cost.

The outcomes of the cost assessment indicate that the combination of higher accuracy and integrity message could represent gains between EUR 0.01 and EUR 0.03 per delivery. The technical analysis and the cost assessment carried out under the project confirms the clear business case for the use of EGNOS and Galileo combined with GPS for position and navigation purposes.

Learn more about the technical outcomes of the study and possible business cases for food delivery and last-mile parcel delivery with drones. For the full article click here.

*The comparison considered drones using GPS and EGNOS within their navigation systems.

Author: Thiago Tavares, VVA Brussels

Photo credit: VVA Brussels