The electric scooter is the latest entrant into the app-based mobility market.
Residents and visitors in the nation’s capital, and in many other U.S. cities, now have access to motorized scooters that rent for as little as $1 plus 15 cents per minute. The services work similarly to the dockless bike systems, allowing users to track down a scooter via an app and to drop it off just about anywhere after a trip is completed. No docking is required.
The new transportation product is touted as another option for commuters to make first- and last-mile trips in complement to traditional transit.
“Today, 40 percent of car trips are less than two miles long. Our goal is to replace as many of those trips as possible so we can get cars off the road and curb traffic and greenhouse gas emissions,” said Travis VanderZanden, founder and chief executive of Bird, which recently announced plans to bring scooters to 50 U.S. markets by the end of the year. The company is in several California markets and has raised $100 million to expand to cities outside the state, including the District.
In a study, the researchers used two types of neural networks — computational systems modeled on the human brain — that analyzed patterns of taxi demand. This deep learning approach, which lets computers learn on their own, was then able to predict the demand patterns significantly better than current technology.
“Ride sharing companies, like Uber in the United States, and Didi Chuxing in China, are becoming more and more popular and have really changed the way people approach transportation,” said Jessie Li, associate professor of information sciences and technology, Penn State. “And you can imagine how important it would be to predict the taxi demand because the taxi company could dispatch the cars even before the need arises.”