By Larry Greenemeier
Amazon, Uber and other tech giants want to fill the skies with small autonomous aircraft ferrying packages and people from place to place. For that to happen, these robotic drones—also called unmanned aircraft systems (UASs)—need an air traffic control system to keep them from crashing into buildings, human-piloted aircraft or one another. NASA is developing a UAS Traffic Management (UTM) network with several other organizations that the group plans to finish testing next year. Uber, in particular, has a lot riding on the UTM’s success—the ride-sharing company made several announcements last week to promote its proposeduberAIR taxi service. Big questions remain, however, as to whether and when any monitoring and management system will be able to handle the expected volume of large self-flying aircraft, which will be traveling great distances to deliver everything from pizzas to passengers.
Uber is onboard with NASA, at least. The company announced at its Elevate aviation conference in Los Angeles on May 8 and 9 it had signed an agreement to provide NASA with details and data about the inaugural uberAIR service it has planned for Dallas–Fort Worth. In return, the agency will use Uber’s data to make computer simulations of small passenger-carrying aircraft flying over the Texas Metroplex during peak air traffic times. Uber will analyze those simulations to help plan air taxi management in the already crowded skies over Dallas as well as Los Angeles and Dubai—the other cities hoping to start testing uberAIR by 2020.
Uber is targeting urban areas that have a population of more than two million people and a density of more than “2,000 people per square mile,” according to documents on Uber’s Web site. The cities must also have a large and dispersed layout that allows air taxis “to offer significant time-saving benefits at speeds of” 240 to 320 kilometers per hour. The company also points out flights will go from “node to node rather than point to point,” meaning there will be specific—rather than random—pickup and drop-off sites.
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