Microsoft Research Blog

The Microsoft Research blog provides in-depth views and perspectives from our researchers, scientists and engineers, plus information about noteworthy events and conferences, scholarships, and fellowships designed for academic and scientific communities.

Microsoft Azure helps researchers predict traffic jams

April 2, 2015 | By Microsoft blog editor

More than half of the world’s population now lives in cities and suburbs, and as just about any of these billions of people can tell you, urban traffic can be a nightmare. Cars stack up bumper-to-bumper, clogging our highways, jangling our nerves, taxing our patience, polluting our air, and taking a toll on our productivity. In short, traffic jams impair on our emotional, physical, and economic well-being.

Can big data beat big traffic?

A study by the Brazilian National Association of Public Transport showed that the country’s traffic exacted an economic toll of about US$7.2 million in 1998. Unfortunately, it’s only getting worse; there are now about three times as many vehicles in Brazil, making traffic exponentially worse, according to Fernando de Oliveira Pessoa, a traffic expert in Belo Horizonte, Brazil’s sixth-largest city.

Microsoft Research has joined forces with the Federal University of Minas Gerais, home to one of Brazil’s foremost computer science programs, to tackle the seemingly intractable problem of traffic jams. The immediate objective of this research is to predict traffic conditions over the next 15 minutes to an hour, so that drivers can be forewarned of likely traffic snarls.

The aptly named Traffic Prediction Project plans to combine all available traffic data—including both historic and current information gleaned from transportation departments, Bing traffic maps, road cameras and sensors, and the social networks of the drivers themselves—to create a solution that gets motorists from point A to point B with minimal stop-and-go. The use of historic data and information from social networks are both unique aspects of the project.

By using algorithms to process all these data, the project team intends to predict traffic jams accurately so that drivers can make smart, real-time choices, like taking an alternative route, using public transit, or maybe even just postponing a trip. The predictions should also be invaluable to traffic planners, especially when they are working to accommodate traffic from special events and when planning for future transportation needs.

Achieving reliable predictions will involve processing terabytes of data, which is why the researchers are using Microsoft Azure as the platform for the service. The exceptional scalability, immense storage capacity, and prodigious computational power of Microsoft Azure makes it the perfect resource for this data-intensive project. And because Microsoft Azure is cloud-based, running the Traffic Prediction service on Azure makes it accessible to all users, in real time, all of the time.

To date, the researchers have tested their prediction model in some of the world’s most traffic-challenged cities: New York, Los Angeles, London, and Chicago. The model achieved a prediction accuracy of 80 percent, and that was based on using only traffic-flow data. The researchers expect the accuracy to increase to 90 percent when traffic incidents and data from social networks are folded in.

So the next time your highway resembles a long, thin parking lot, you might calm yourself by contemplating how Microsoft Azure and the Traffic Prediction Project might help you avoid such tie-ups in the future.

—Juliana Salles, Senior Program Manager, Microsoft Research

Learn more

Up Next

Data visualization, analytics, and platform, Medical, health and genomics

Helping proteomics scientists share peptide data: Azure does the heavy lifting

Scientific research breakthroughs are often achieved when many different scientists, in different labs and organizations, work together on a single task. That happened at the turn of the 21st century with the Human Genome Project, where human DNA was mapped for future reference and is now key to many breakthroughs in medicine. This is happening […]

Vani Mandava

Director, Data Science Outreach

Data visualization, analytics, and platform

Transportation Data Science at Microsoft

By Vani Mandava, Director, Data Science Outreach, Microsoft Research The National Science Foundation (NSF)-supported Big Data Innovation Hubs launched a National Transportation Data Challenge with a kickoff event in Seattle in May 2017. Microsoft Outreach, through its partnership with the Big Data Hubs organized an Azure workshop and participated in a panel discussion on ‘How […]

Microsoft blog editor

Data visualization, analytics, and platform

Microsoft continues to support data science research with $3M cloud credits to NSF BIGDATA program

By Vani Mandava, Director, Data Science, Microsoft Research The National Science Foundation has launched a new solicitation in 2017 for the advancement of data science research and applications. The solicitation, titled Critical Techniques, Technologies and Methodologies for Advancing Foundations and Applications of Big Data Sciences and Engineering (BIGDATA), is inviting proposals under two categories: Foundations […]

Microsoft blog editor