Researchers at the University of Maryland have developed an algorithm to route and schedule air mobility flights in future smart cities to maximise the number of passengers transported.

Maryland University professors Raghu Raghavan and Bruce Golden analysed the logistics associated with running a system of eVTOLs within future smart cities, focusing on of routing and scheduling. They found three key challenges for electric flying taxi firms in the early phases: demand, time windows for customers, and the taxis’ battery management constraints.

Taxi data from Washington DC was used to illustrate their findings in a real-world environment. “When you do research like this, you’re looking into the future, and you want to make sure your assumptions are as solid as they can be,” Golden said.

“It ties into the concept of smart cities where getting around—going from one place to the other—is going to be much easier and sustainable, while allowing for dense urban areas,” said Raghavan.

The researchers developed an algorithm that electric flying taxi companies can use to schedule passengers in the same way that ground transportation taxi firms do. “The algorithm allows them to schedule their service to maximise the number of people they transport,” said Raghavan. “That then translates into maximising revenue generated from those passengers.”

The researchers found that passengers wouldn’t want to deal with long waits for these taxis to arrive, just as they don’t like waiting for ground transporting taxis or subways. Golden likening it to riding the Metro in the nation’s capital. “If you had to wait more than 10 minutes from the Red Line to the Blue Line you’d say, ‘This is crazy!'”

There’s also the battery issue. It takes time to recharge the battery that runs the electric flying taxis and fare scheduling must be cognisant of that. “You fly from place A to B just like you drive your Tesla,” said Raghavan, “it’s discharging, so you can’t just keep flying it.”

Once the taxi lands at its first destination, the second is determined by how much power the battery has left or a decision must be made to charge the taxi so it can make it to the next stop. “You’ve got to bake that in” to the fare scheduling mix said Golden.

The research developed formulations for successfully routing electric flying taxis over a time-expanded network. One of the reasons Golden, Raghavan, and Oden were inspired to pursue this work was the promise that UAM shows for improving our daily lives. It can reduce the time and cost of moving people and goods in and around cities.