|Less Traffic on Your Commute? Thank Big Data
Image: AP Staff/Associated Press
By Eli Epstein2014-10-01 18:42:27 UTC
Last year, Los Angeles became the world's first major city to synchronize all of its traffic lights, a nearly 30-year, $400 million project that allows the city's traffic operators to instantaneously turn red lights green and control signals in congested areas.
Though the early results of the program have been favorable — travel speed has increased 16%, while travel time is down 12%, according to a California State Senate report — Los Angeles, much to the chagrin of its nearly 4 million residents, remains the nation's most gridlocked city, according to a study by Tom Tom.
See also: 25 Technologies Every Smart City Should Have
That's not necessarily a bad thing, which the results of the state senate report show. Still, experts say, synchronization is by no means a congestion panacea.
What is? Well, that's a tricky question. There are technological innovations that will make our vehicles smarter, as well as radical economic theories that could zap rush-hour gridlock in some places, but for both ideas to work together, our cities and habits first need to become more technology-driven and interconnected, experts say.
Here's how they're working to make that vision a reality.
Congestion percentage is computed by comparing traffic data from free-flow driving times and rush hours. If a city has 100% congestion, for example, rush hour journeys there are two times as long as free-flow trips.
For decades, transportation economists and engineers have understood that if they want to reduce congestion (and really, who doesn't?), they first need to look granularly at individual driving habits and the routes commuters take to get from point A to point B.
To do so, engineers began collecting data to find out how many cars were on a section of thoroughfare, and how fast a particular vehicle was traveling. Not all data collection is created equally, however.
In Los Angeles, which was one of the world's first cities to apply computational research to traffic, engineers in the 1980s installed wires, called loop detectors, below the pavement to monitor traffic flow. With that information, they were able to tinker with signals and plan routes for major events — like the 1984 Summer Olympics — before other major cities had the ability to do so.
Though still in use today, loop detectors have been lapped by their technological successors, mainly due to the high price of maintaining underground telemetry and the ability of newer technologies to capture more detailed information.
In the years after the first cables were installed underneath the asphalt of Los Angeles, city and state DOTs across the country introduced a variety of methods to better capture vehicle data. For instance, a toll tag, the same device you place onto your windshield to breeze through a toll booth, can also be used to determine the average speed of your vehicle between two points. With that information, traffic engineers are able to analyze travel time reliability and spot incidents.
More recently, faced with shrinking budgets, DOTs have gotten more inventive, using wireless sensors along major thoroughfare to pick up Wi-Fi and Bluetooth signals from devices in passing vehicles. Those sensors anonymously extract speed data, which they send back to a traffic control center. Along with images taken from signal-mounted cameras, that data helps engineers tinker with traffic light timing.
“For sensing traffic flow, it's not just Bluetooth or Wi-Fi; it's also cellular-based data,” says Tony Voigt, a research engineer at Texas A&M's Transportation Institute. The city of Houston, for instance, has been using Bluetooth signals for nearly five years to aggregate data and compute average travel times, Voigt says.
“There are various options that didn't exist five years ago that are beginning to be leveraged to provide better information,” he adds.
While advanced, toll tag and Bluetooth technologies aren't perfect. One drawback to those methods of data collection is that they're mainly implemented on major roadways. That's problematic for engineers who want to devise the best alternative routes for delays and accidents — detours that usually sweep through non-connected backroads.
“The ability to sensor every roadway just doesn't scale,” says Jim Bak, senior PR and marketing manager at Inrix, a Seattle-based company that anonymously collects travel data from drivers’ connected devices and makes predictions based on those figures and variables like weather, construction and special events.
“We want be able to get traffic reports on every road, not just where governments have been able to invest the money and time to maintain sensor networks. That’s traditionally only been on highways and interstates,” Bak adds.
To help drivers in those gray zones, Inrix scoops up user data and cross-references it with historical trends and crowdsourced incident reports. In the event of a traffic-crippling incident, Inrix is able to pinpoint not only the location of the accident, but also where the traffic queue begins. That last part is critical, Bak says.
"If you don't know where the back of the queue is, you don't know how to avoid it," he says. "The challenge DOTs find themselves in is that accidents and work zones tend to create accidents. People will just drive right into the back of a traffic queue not knowing that it's there."
Today, Inrix works with 40 state DOTs, including the Indiana Department of Transportation, which is now able to discern the back of a traffic queue within 100 yards and send state troopers there to warn drivers to slow down.
"You and I sit here and think that's a pretty rudimentary solution after you have all this technology and big data working for you," Bak says. "The beauty of that, though, is that ultimately, as we get more connected cars on the road, we'll be able to send these messages directly to drivers in their vehicles."
While retrieving data from drivers and roads (and one day cars themselves, most likely) is a major step in decluttering our roadways, those methods are unlikely to eradicate congestion (especially in major cities) without accompanying policy changes, some experts say.
One of them is Charles Komanoff, a policy analyst and mathematician who, since 2007, has labored tirelessly to create a spreadsheet with nearly 500,000 cells, named the Balanced Transportation Analyzer, that calculates the savings — in both time and money — of imposing a "congestion fee" to enter Manhattan’s Central Business District.
The BTA doesn't just compute traffic density and time. Komanoff has made his calculations (as well as the Move NY toll rebalancing plan it's pegged to) nearly all encompassing and elastic, factoring in how taxis, parking delays, and construction contribute to congestion and how models change when taking into consideration time of day, travel demand and varied transit fares.
Why all the mathematical legwork? According to Komanoff's analysis, a typical round trip to the CBD during rush hour slows down other drivers by an aggregate of nearly three hours, an outcome many drivers have no idea they're contributing to.
“When traffic is light or even moderate, those time costs are generally modest — my trip hardly slows down traffic, and the other vehicles are few enough that any delays caused by my driving can't add too much,” Komanoff writes in his breakdown of the BTA. “But in the heavy traffic conditions that typify congested NYC roads — especially in the Manhattan Central Business District and on the approaches to it — those costs can be substantial.”
If there was a fee to enter the CBD by car during rush hour, however, non-essential trips would be incentivized to avoid roadways during busy periods, Komanoff says. He estimates that the average car speed within the CBD on weekdays will increase by 15-20% if a congestion fee was to be implemented.
While some might say a tariff to enter Central Manhattan discriminates against millions of New Yorkers, Komanoff disagrees. On the contrary, he says the CBD and the Move NY plan makes New York as a whole — not just Central Manhattan — more accessible.
That's because as part of the BTA and Move NY, transportation officials would take in enough revenue from CBD tolls to be able to halve toll fees at as many as seven major New York bridges (many of them conceived by Robert Moses) that don't lead directly into the CBD.
“Those MTA [Metropolitan Transportation Authority] bridges have become a real cash cow,” Komanoff tells Mashable.
“The [MTA bridge] tolls are also a sore point for people living in outer parts of the city,” he adds. “Those trips have no truly viable mass-transit alternative, whereas trips in and out of the CBD do.”
After drastically cutting toll prices at seven major MTA bridges and instituting a CBD toll (among other measures), the BTA and Move NY plan estimates that officials will have nearly $1.5 billion to use towards improving New York's aging transportation infrastructure — primarily its subway system. By doing so, Komanoff says, the MTA will be able to avoid onerous tax and fare increases that normally fund transportation improvements.
“The subway system is not only the number one transportation mode; it’s also the one that’s the most capital intensive,” he says. “If you make transportation more efficient, in New York or any other city, you are going to attract and retain jobs, residents and households and tourism.”
What will your commute to work be like in 2030? Will you use public transportation to get there? What about a bike-sharing program? Will you use a vehicle (possibly an electric one) that can find optimal routes and avoid parking delays in real-time?
Boyd Cohen, an urban strategist and the director of innovation at the Universidad del Desarrollo in Santiago, Chile, says the future of transportation will likely involve the integration of public and private modes of transportation to create the most efficient itinerary.
“In the future, where we really need to get is to optimize sustainable and quick transit alternatives using multiple modes of transportation,” he says.
For example, Cohen imagines, GPSs, using real-time traffic data, could be able to determine the best route of travel on a number of modes of transportation. The software could tell drivers the best place to park their car so they can board a nearby light rail and then depart near a bike share. It could find them the closest electric car charging station and a curbside parking spot that won’t lead to further congestion.
Or, as Sarah Kaufman, an adjunct professor at New York University’s Rudin Center for Transportation Policy and Management, suggests, an app could wake a person up earlier than they normally would because its AI has detected a train delay and the best alternative route is by bike.
Connecting modes of transportation like this, experts assert, is how our daily commutes and, consequently, our cities, will become smarter.
“I think we’ll see full on integration between rapid transit, bus, bike and train,” Cohen adds. “That’s when we’ll have reduced congestion and reduced impact on the environment.”