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From Aviators to Apps: The Evolution of Traffic Data

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Bay Area drivers have always needed information on traffic. How that information is collected has changed over the decades. (Justin Sullivan/Getty Images)

Commuting on Bay Area roads is a pretty awful experience. Personal finance site WalletHub recently ranked it as the second worst place to drive in the country.

Many have turned to using GPS-powered apps like Google Maps or Waze to prepare for slowdowns or find detours.

But tracking the roadways wasn’t always this easy.

The Early Days of Traffic Reporting

After World War II, the Bay Area became a much more sprawling place as rural areas were transformed into suburbs. A network of freeways sprouted up, and by the 1950s, a lot more people were driving cars to get around.

A new demand arose for traffic information, and the easiest way to keep watch on the roadways was from the sky.

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“Helicopter pilots were coming back from their time in the military, whether they were serving here in the States, or in Korea, or later Vietnam,” says John Goodwin, a public information officer with the Metropolitan Transportation Commission. “Traffic helicopters would fly over the freeways and report back to the ground. The drivers would receive this information via their in-dash radio.”

News stations also hired traffic reporters to do a more grueling job: actually sit in traffic.

“Various stations would have a fleet, or sometimes a single car, that was radio-equipped,” says Goodwin. “They would have a reporter travel a prescribed loop and report back how long it took.”

Most news stations could afford their own helicopter and traffic reporters, but those days were numbered.

During the 1970s energy crisis, it became too expensive for news stations to operate a fleet of helicopters to monitor the freeway.

“That led to a sharing of information,” Goodwin says. “Rather than each individual station having its own helicopter, you could have a traffic service, and that would provide information to multiple radio or television stations.”

Traffic reporters once used white boards to track the commute. (KRON)

FasTrak Changes the Game

Between 1999 and 2000, traffic data made a quantum leap.

“The FasTrak system introduced first at the Golden Gate Bridge, and then ultimately on the rest of the bridges, became a way to gather information,” Goodwin says.

As part of its deployment of the 511 traffic information system, the MTC set up over-the-road antennae around the Bay Area that could track how long it took a car with a FasTrak transponder to get from Point A to Point B. They’d then aggregate and anonymize the data, and provide precise point-to-point travel times throughout the region.

“That became more effective, and more efficient, and consequently the number of traffic helicopters declined,” Goodwin says.

The system had a flaw, though. Because it depended on cars having FasTrak tags, it worked better where more residents had FasTrak — usually in the communities closest to the toll bridges.

Travel times were least accurate in places like eastern Contra Costa County, eastern Alameda County or in the South Bay, Goodwin says.

The FasTrak method of traffic monitoring would stick around only for a short time. By 2007, cellphones started to become increasingly outfitted with GPS capability.

The Problems Navigation Apps Cause

These days, GPS data powers most of the sources that commuters and traffic reporters use.

“Any app that you have turned on that has some form of geolocation — whether it’s a navigation app, whether it’s an app such as a social network, whether it’s a game — it has the ability to collect GPS data and potentially to send it to a third party,” says Alex Bayen, a UC Berkeley professor and the director of its Institute of Transportation Studies.

Your wireless service provider could be sharing your location data or even the company that makes your car. Chances are good if you’ve got a phone in the car, you are a data point — perhaps many times over — simultaneously a provider and consumer of traffic data.

The move to GPS data has vastly improved the quality of traffic data. But studies show there is a downside.

“The number one problem it has created is the emergence of new traffic jams in residential areas that didn’t used to be there before,” says Berkeley’s Alex Bayen. “That’s a big problem in California and all around the world.”

You know the scenario. There’s a wreck up ahead, and the app says you can save seven minutes by taking a detour through some small town. You exit the highway … along with a lot of other drivers.

Suddenly there’s a new traffic jam on a street not equipped to handle such a high volume of cars.

These apps’ lack of predictive routing is the source of the problem. They don’t think ahead to the traffic jam they’ll create by sending 200 cars down a residential street.

Some cities have started to fight back by taking steps to make their town a less appealing detour. They’ve intentionally slowed traffic by adding stop signs or changing the timing of traffic lights.

“We’re at the beginning of a war between cities and these apps,” Bayen says.

He’d like to see cities and app developers come together to solve some of these problems.

“I think the only way it can [get] better is if we have the proper institutional framework for these apps and services to work in coordination with public agencies,” he says.

One idea? Specify how many cars that apps can route along certain roads.

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