Austin’s Smart City Challenge Proposal: What’s Next?

Photo credit: Deborah Cannon, Austin American-Statesman

U.S. Secretary of Transportation Anthony Foxx, right, talks with Austin Mayor Steve Adler after a May 17 meeting to discuss the city’s application. Photo credit: Deborah Cannon, Austin American-Statesman

In June, the USDOT announced that the winner of the Smart City Challenge competition was Columbus, Ohio, disappointing many in Central Texas who were hoping Austin would snag this city-changing opportunity. The USDOT had pledged up to $40 million to one city that would define the concept of a “Smart City” and become the country’s first city to fully integrate innovative technologies—such as self-driving cars, connected vehicles, and smart sensors—into their transportation network. Austin was one of seven cities named finalists in this competition (out of 78 that applied). As part of its Smart City Challenge proposal, the City of Austin laid out a plan involving automated and connected vehicles, intelligent sensors, open data, real-time traveler information, and a suite of mobility options for travelers. CTR’s proposed role within this plan was to create and host a Data Rodeo—a single point of access for regional transportation data and analytics. In fact, CTR researcher and director of its Network Modeling Center, Jen Duthie, was called in May to testify on CTR’s role in Austin’s proposal for the Smart City Challenge at a hearing held by the Texas House of Representative Transportation Subcommittee on Long-term Infrastructure Planning. State Representative Ron Simmons invited Duthie to speak in response to an article she co-authored with CTR Director Chandra Bhat titled “Texas could be an incubator to solve national transportation problems.” In the article, Duthie and Bhat address how researchers and government entities can work together to create an effective transportation model in Austin that can be replicated nationwide.

Indeed, participating in this competition brought together diverse resources, as the City of Austin created a statewide coalition of government and private industry partners to generate next-generation mobility solutions. The city’s proposal partnered such entities as CTR, Capital Metro, the Texas Department of Transportation, Austin Energy, the Texas A&M Transportation Institute, the Southwest Research Institute, the Central Texas Regional Mobility Authority, the Rocky Mountain Institute, Travis County, and numerous community and private sector partners. Other UT resources involved were the Austin Technology Incubator (UT’s multidisciplinary tech startup incubator),  and the LBJ School of Public Affairs, who can offer advice on how to ensure advances in transportation technology and systems are accessible to all city residents. Some of the city’s plans included pushing for a pilot program for self-driving cars, lowering IH 35, electrifying more of the city’s fleet, and creating an open market for ride-hailing apps. Austin Mayor Steve Adler said even if the city doesn’t win the smart city challenge, Austin’s proposed projects will still be completed (although the city will have to find the money locally).

“All of these things are going to continue to move forward and they are exciting,” said Adler. “Even though we didn’t win, the benefits of having gone through the process will pay dividends to Austin for years…We have come out of this process much better off than when we began.”

Photo credit: Miguel Gutierrez Jr., KUT News

NMC Director Duthie leads the Data Rodeo project. Photo credit: Miguel Gutierrez Jr., KUT News

Duthie agrees, noting that “the challenge has been a game-changer.”

Although Austin didn’t win the competition, work proceeds apace on the Data Rodeo, as CTR collaborates with UT’s Texas Advanced Computing Center and regional partners like the Capital Area Metropolitan Planning Organization. This two-way open data sharing portal will improve how transportation providers, including businesses and government entities, offer effective mobility.

Posted by Maureen Kelly  |  Category : Autonomous/Connected Vehicles