Bell AerOS Shows How Urban Air Mobility Flies
Bell is demonstrating how a smart city of the future could incorporate urban air mobility vehicles running under autonomous control.
The four-rotor version of Bell's Nexus could be all-electric- or hybrid-electric-powered. (Image: Bell)

At this year’s CES show in Las Vegas, which opens tomorrow, Bell will demonstrate a model-sized cityscape with scale flying versions of its Nexus passenger air taxi operating autonomously by Bell’s AerOS urban air mobility operating system. Calling it a “smart city ecosystem,” Bell president and CEO Mitch Snyder explained, “this year, we’re demonstrating what governing, operating, working, and living in a smart city will look like.”


The Bell demo at the CES Mobility Hall is designed to highlight how “mobility as a service” software like AerOS can manage a metropolitan area’s urban air mobility (UAM) activities. Bell intends to offer AerOS, which runs on Microsoft’s Azure platform, to cities to speed up their adoption of UAM capabilities.


Bell has also settled on a smaller version of its Nexus passenger vehicle, with four rotors instead of the six previously shown at CES. The Nexus is designed for all-electric or hybrid-electric power, but is “propulsion-agnostic,” according to Bell, “depending on customer needs.” The four-rotor Nexus will have initially a 60-mile electric range, but that could be greater with hybrid-electric power.


At CES, the smart city demo includes tablet stations where visitors can interact with AerOS and see what how the flying models are interacting. The flying models are not controlled by individuals flying them, but by the AerOS software, which is constantly assessing demand across the scale-size city and deploying the vehicles to meet that demand.


The demo also takes into account problems that inevitably come up during passenger and cargo flying operations, for example, weather events that might require all vehicles to land immediately. AerOS also creates an optimal flight schedule based on goal-seeking optimization algorithms and artificial intelligence to anticipate passenger behavior and desires and the vehicle’s needs for battery recharging to meet the schedule.


“We have to work closely with regulators,” said Snyder. “We’re working on the technology and regulations and with cities to progress this. But we are designing vehicles and maturing the technology, and driving that together.”