The USDOT Has a Big Data Challenge

U.S. Department of Transportation Chief Technology Officer, Maria Roat, was in the news recently discussing a pilot program at the department to determine Americans’ driving patterns using a series of on-board sensors and back-end analytics. The article in which Ms. Roat’s comments appeared did not name the USDOT program conducting the work, but presumably it is part of the Federal Highway Administration’s effort to develop vehicle-to-vehicle (V2V) technologies as part of the Intelligent Transportation Systems (ITS) initiative.

For those unfamiliar with the ITS, it is a massive program to deploy sensor, wireless, and related technologies on roadways and in vehicles to improve highway safety and to promote efficient use of the transportation infrastructure. It is also a program with big money. In fiscal 2015, the FHWA’s Research, Technology & Education Program spent $100 million related to ITS and it requested $158 million more for fiscal 2016. This $158 million is part of the USDOT’s larger ITS request for $935 million over the six years from FY 2016 to FY 2022.

Judging from Ms. Roat’s comments, the ITS program and its V2V component are just getting off the ground. Nevertheless, the amount of data collected so far during the pilot program, “4 petabytes of data, collected from test-drivers who spent about 1 million hours in about 2,000 cars” hints at the vast flood of data that is coming. This data will come from a variety of sensors, both in vehicles and on roadways. It will come in real-time and its flow will be incessant. In other words, the data generated by the ITS initiative will have volume, velocity, and variety, meaning it meets the basic criteria for big data.

So, where will the funding be dedicated for work related to the ITS? Fortunately, the FHWA outlined its programmatic needs for the ITS in its FY 2016 budget request. The major components of this are summarized below, with the fields shaded white being those that seemed to have particular applicability to big data technologies.

In this case, identifying which pieces of the ITS will need analytics capabilities is a loose guess based solely on the title of the program. Those interested in teasing out the potential for spending in each area are encouraged to mine the data here for further information. What can be confirmed at this point is that modeling and simulation expertise, predictive analytics, analysis support, and related services will be required. This is made clear in the Traffic Analysis Tools Primer available on the ITS website.

Vendors seeking big data opportunities need look no further than the ITS. In fact, big players like IBM and Intel are already positioning themselves to reap the benefits of the Internet of Things-driven, big data-generating ITS. Admittedly, a high percentage of the funding the FHWA has requested for ITS will go to grants for research and development. A lot of dollars, however, will also flow into contractor support making the ITS one of the potentially most lucrative big data-related initiatives out there.