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Calling all cars: cell phone networks and the future of traffic


Ask someone what they think the future of driving is, and the most likely response involves self-driving cars. And it's true that sensing and autonomy are dramatically changing the modern car, but there's another information revolution taking place outside the windows. Cheap sensors and network availability are not only making individual cars smarter, but they're also boosting the brainpower the environment cars drive in.

Networks of sensors connected by the Web are making it possible to monitor traffic, parking availability, air pollution, road quality, and more in real time and across large distances. Traffic monitoring in particular has been revolutionized by these changes. This kind of data gives drivers real-time travel time predictions, makes it possible to create smart roads where tolls and signals can adapt to changing conditions, and provides urban planners with accurate and detailed pictures of traffic usage and its effects, improving city layout and planning for the future.

One of the most widespread and powerful sensors is the mobile phone. Equipped with GPS and connected to the Internet, modern smartphones are an important source of information that many companies use to provide traffic data. Google Maps, for example, makes extensive use of data collected from users on mobile phones.

Mobile Millennium was one of the first large-scale phone-based traffic monitoring projects in the US. An ongoing pilot project run by Nokia, NAVTEQ, and UC Berkeley started in 2007, its goal is to develop and demonstrate technologies needed for large-scale data collection for traffic monitoring. The project combines data from a smartphone app distributed to the public and traditional traffic sensors to provide accurate real-time monitoring of traffic conditions in the San Francisco Bay Area.

The Mobile Millennium traffic monitoring software. Source: UC Berkeley.

Designing and running these sensor networks is no trivial task. Data is flooding in from many different sources in many different places, and useful data has to be separated from noise. Algorithms and models are needed to fuse the incoming data into a comprehensible whole, and protecting individual privacy is also a major challenge. Yet the potential gains are huge, so there is an unceasing demand for more and better data.

In this article, Ars goes behind the scenes at Mobile Millennium to examine the technology behind a distributed sensor network. We'll look at how the system is designed to protect user privacy, examine how data from thousands of mobile phones and hundreds of static sensors are combined to measure traffic flow, and look at how this technology will impact the future of driving.

An intelligent highway

The most obvious use of traffic data is to give drivers options for reducing the effects of traffic jams and accidents, either by taking alternate routes or simply by changing their travel times. Trip-planning software already can use traffic speed information to minimize travel time or fuel usage over a trip, and future hybrids and electric vehicles might use traffic predictions to help the onboard computer optimize battery usage.

This kind of real-time data also lets civil engineers create traffic control schemes that react intelligently; for example, smart signals could eliminate the need to wait at red lights and empty intersections. Larger scale efforts might involve roads that actively change direction in response to changing traffic flows.

The data is also of more than just immediate importance. Having good data on current traffic and road usage is vital to predicting future patterns of traffic, which is important for planning purposes. Ars recently explored the issues related to congestion pricing, one of the most popular tools for alleviating congestion. Congesting pricing uses dynamic tolls that are adjusted according to road usage to try to reduce traffic during peak conditions. The success of such schemes is heavily dependent on being able to measure the effects of pricing changes on driving patterns.

Finally, accurately measuring traffic is also useful beyond the immediate realm of driving. Cars and roads have a huge impact on our societies, and traffic has many secondary effects. For example, traffic is a major source of potentially harmful noise, and the generation of noise maps of the city is one of several projects underway that piggybacks on the Mobile Millennium data and network. By correlating noise patterns to population maps, it's possible to assess the impact of noise on the city's people. Cars are also a major source of air pollution, and traffic data can be correlated and combined with measurements taken by pollution sensors to build a map of pollutants produced by cars around the city.

Going mobile

For a long time, traffic sensing was mostly reliant on static sensors. Inductive loop detectors—metal rings embedded in the road—detect the metal in cars that pass over them. Traffic cameras are another common sensor type, and the RFID tags used for electronic toll payment can be tracked to provide data.

These types of sensors are generally pretty accurate, but fixed infrastructure is expensive to deploy and operate. When these sensors break, they're also expensive to repair and replace, so they're typically placed at key places like intersections and highway on- and off-ramps. This means that when traffic conditions change, like when an accident occurs, the changes aren't detected until their effects propagate back through the traffic flow upstream to a sensor.

The need for ever more data from ever more widespread sensors has meant that going to mobile sensors is a necessity, and mobile phones are an obvious choice. It's an oft-quoted statistic that worldwide, there are more cell phones in use than toothbrushes. And an ever-growing fraction of those phones, especially in the US, are smartphones, equipped with GPS and Internet connectivity.

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