The burgeoning movement to figure out when and where congestion happens has a new player backed by a powerhouse tech company.
Urban Engines, a Google Ventures-backed startup in based in Los Altos, Calif., is pushing new software called the “Space/Time Engine” that seeks to aggregate real-time traffic data and then feed it into predictive models. The goal is to give users the ability to see what route will likely be the best to send a package along, or drive a fleet vehicle through, or simply avoid congestion based on what time of day it is and what’s happening in the area. The engine supplements its information with data about things that impact traffic flows like weather and major events.
And the company appears to be gaining ground. It announced via press release on Jan. 28 that it has secured business with the train-running Bay Area Rapid Transit, as well as the international private-sector firms NEC, Softbank and Delhivery.
The firm’s model relies on the growing Internet of Things, which involves collecting more data than ever before through a network of sensors in cellphones, cars, on street lights and sometimes in garbage bins.
“Our world is constantly changing with variances every second,” the press release reads. “The best route and time for getting from one end of a city to another is not static, so the best business decisions shouldn’t be either.”
Though Urban Engines bills itself as the only company that weaves in information about when traffic is congested and not just where traffic is congested, it is working into a niche market of traffic analytics that already has some established players. INRIX recently announced contracts with government entities in Colorado and California to provide real-time traffic maps, and HERE is working in Colorado’s mountain-hugging roads to push information to vehicles approaching traffic queues. There are government entities working on their own project as well, with the U.S. Department of Transportation sponsoring vehicle-to-vehicle and vehicle-to-infrastructure connection pilots related to congestion in cities such as New York and Tampa.
Adding in a more robust system for figuring out when congestion happens and not just where makes the data more useful for a number of purposes, Urban Engines posited in the press release.
“Congestion isn’t limited to single commutes, but the collective impact of how each car, bus, bike, parcel, delivery service, and/or person navigates busy city streets,” the statement reads.