Traffic studies and transportation plans may have gotten easier. A digital traffic engineering and planning solution offers a new approach.
This method of obtaining traffic data promises a large amount of data quickly. By aggregating location data from our mobile devices and vehicle GPS, we can now make informed traffic analysis and transportation planning decisions in the blink of an eye.
According to Graham Johnson, senior traffic engineer, traditional data field collection involves spending time in the field or in front of a computer terminal manually recording vehicle license plates for an origin-destination (OD) study, with video or pen and paper. After, information is entered into a database or spreadsheet and sorted.
Another OD study method is sending out surveys, through the mail or online, asking drivers about their driving habits, direction, routes, etc. Setting up a series of cameras at an intersection or along a roadway is another method—the footage is then logged and studied before observations can be made about an area. A ‘truck trace’ is another, older method of capturing commercial traffic data. According to Johnson, during a truck trace, traffic engineers follow a truck on its route through an area, recording data on its movement. Other manual methods of logging roadway traffic data include laying down road tube sensors that record data when driven over—you’ve likely seen the black tubing stretched across roadways.
“Each method has its own approach,” Johnson says. “Every traffic analysis situation requires something different.”
These processes take time to complete. The number of people who respond to mailed or online surveys are seldom enough to make informed decisions. While road sensor data is good, the sensors are not typically placed everywhere throughout a city or along a corridor. What’s more, studies like these are usually only done over one or two days’ time.
Now, we can better understand traffic patterns in minutes through digital analytics platforms that offer a variety of services. The platforms offering these traffic solutions gather data by accessing location and speed information shared by cell phone apps and in-vehicle navigation systems. These are the kinds of apps that ask for permission to access your phone’s location information. The service providers then share the information with the digital analytics platforms. To help quell privacy concerns, all personally identifying information about the cell phone user is anonymized before being shared with the platforms.
Cell phone data in particular is ubiquitous and very accurate. It seems that today, nearly every person has a cell phone on them. These digital analytics platforms combine the obtained cell phone data with traditional traffic data counts via algorithm—resulting in hyper-localized, accurate information. With access to 365 days of traffic data from millions of vehicles across four million miles of U.S. roadways, traffic planning options are nearly endless.
“We now have access to a year’s worth of travel patterns and traffic data to better help us make decisions,” Johnson says. “Whereas before the data collected would typically be for only a couple of days or even just a couple of hours.”
To use the technology, users set up a variety of queries to answer traffic-related questions. There are answers to traditional traffic engineering questions including: traveler origin and destination patterns, destinations of drivers using a certain off ramp over a period of time and what roads are most used in a specific area. The platforms can also figure out the percentage of travelers along a specified route that are going from one place to another. Traffic engineers can also use the data provided by the platforms to suggest better informed detours to move traffic onto during road construction projects.
“One of the biggest areas we’ve used these programs for is OD studies,” Johnson says. “It helps clients save money on those types of projects.”
One reason OD work well using cell phone data Johnson says, is because you can log many more trips over a longer period of time than through manual means.
With a simple OD setup using cell phone data, an intersection turning movement count can be easily estimated based on vehicle turning percentages and existing Average Annual Daily Traffic (AADT) data. This information can be used in a quick traffic analysis situation where it isn’t feasible to do a manual count due to time or financial constraints.
The platforms are continually working on new ways to utilize the data. They’ve developed algorithms that can estimate, to a high degree, AADT data on almost any roadway, without having to set road tubes.
The Minnesota Department of Transportation (MnDOT) wanted to better understand the travel patterns of drivers in and around the City of Glencoe, as well as on the adjacent Highway 22. The highway enters the City from the northwest, takes a circuitous jog, and exits the City on the southwest side. Officials wanted to better understand the routes travelers were taking through the City as well as the percentage of drivers that continued on through the City to the east and those that stayed on the official Highway 22 route. So MnDOT and SEH conducted an origin-destination study using the “big data” from cell phones to track driver behavior through the area. This study had a huge cost savings compared to a manual license plate OD study.
During the planning stages of the study, the City and MnDOT wanted to know the percentage of vehicles driving along Highway 22 that actually stayed on the roadway as it entered and exited the City to the south. At that time, the most viable data source was from commercial vehicles and was the only source used. However, since the completion of the study the platforms have greatly increased the viability of routing cell phone based data.
“What we found out is that the majority of commercial vehicles driving on Highway 22 traveled through the City of Glencoe, onto Highway 212 and out of the City,” Johnson explains. “Very few, about four percent, actually stayed on Highway 22 after it circled through the City, exiting to the southwest.”
Armed with this knowledge, the City is incorporating the data into their overall transportation plan study, designed to better lay out their roadways for future travel accommodations as well as current road construction projects that were in the works.
“At the beginning of the process, some thought a western bypass may help alleviate traffic through the city,” Johnson says. “But what we found out is that very few people were actually traveling that way.”
As with any technology, cell phone data has its drawbacks when used for traffic engineering. In order for it to work, there has to be a cell phone connection. And, it can only track users that have apps installed with location tracking set up. Perhaps even more obvious is the fact that the driver has to physically have a cell phone on them. Because of these limits, the data from these platforms can only be considered a sampling.
“Drivers must have a phone with them. The phone has to be turned on, it has to be getting a signal and pinging off towers or that driver isn’t being counted,” Johnson says.
Vehicle GPS location data is more accurate than cell phone data. Data from commercial vehicles is widely used because most are equipped with GPS devices. Personal vehicle GPS data is available, but typically results in low trip numbers on the platforms. This data should become more widely available as the personal vehicle fleet turns over and more vehicles are equipped with GPS.
Despite obvious advantages using driver cell phone data, there is still a place for tried-and-true manual traffic data collection methods. According to Johnson, a manual traffic count at an intersection or on a section of roadway will be more accurate than using cell phone data—as you’re accounting for up to 100 percent of the vehicles passing through that particular area, and not just a sampling.
Ask any traffic engineer about the future of traffic and you’re likely to hear something about driverless or autonomous vehicles. So where does cell phone and GPS data come in? Johnson says it may not be the cell phones themselves but the way in which everything is transmitting data that will come into play in the future of our roadways.
“Cell phones communicate data with the world at large faster and more efficient than ever before,” he says. “With the always on connections of GPS, Wi-Fi and internet access, we’re transferring data faster now than ever before.”
Today, we have the ability to monitor traffic congestion in real time. We can also monitor travel times, parking availability and even road conditions through a variety of technology. As all of these sensors become more powerful and pervasive, engineers and planners can make more adjustments to roadway operations on the fly and offer up-to-the-second condition information to offer a safer driving experience
The information that we get from cell phone data today is just the beginning. Where we go from here is really only limited by our imaginations.
With advancements in cell phone and vehicle GPS data collection, engineers and planners can quickly and efficiently collect traffic data in a fraction of the time of traditional manual methods and across much longer time spans.
Graham Johnson, PE*, PTOE is a senior traffic engineer focused on the future of mobility while recognizing the importance of tried-and-true methods that help people get from one place to another. Contact Graham