Do you speak V2V? Understanding the language of connected vehicles
- By Matt Leonard
- Aug 03, 2017
As cities look to incorporate connected vehicle technologies in their smarter futures, they should keep an eye on the University of Michigan's connected vehicle research at its Mcity test bed. A public-private partnership between the university and Michigan's Department of Transportation, Mcity is a 32-acre simulated environment that features both urban and suburban areas, including roads with intersections, traffic lights, signs and sidewalks designed to evaluate the capabilities of connected and automated vehicles and systems. UM researchers are also gathering real-world traffic data from about 30 roadside units throughout Ann Arbor.
Huei Peng, a mechanical engineering professor at the university and the director of Mcity, spoke with GCN about how cities might plan for the future of connected vehicles.
This interview has been edited for clarity and length.
What is the enabling technology for connected cars?
We are largely talking about DSRC: dedicated short range communication. Frequency was set aside in 1999, and after that -- 17, 18 years -- there were efforts to decide how to divide the spectrum into different channels and what should be broadcast in each channel.
Right now the standards are defined and stable. All of the top car companies sit down in Society of Automotive Engineers subcommittees to talk about it.
In the meantime, the [U.S.] Department of Transportation has a plan to require DSRC. They’re currently working on it, and, if announced, it could become a Federal Motor Vehicle Safety Standard, just like airbags or rearview mirrors.
Are there any cars that have implemented it already?
Yes, there is one, and that’s the General Motors Cadillac CTS. Japan uses a different frequency, but Toyota already offers DSRC in three of its Japanese models as an option.
How will DSRC be used?
The first application is in vehicle-to-vehicle communication. Cars in close proximity can use an electronic brake light that broadcasts that braking information to other cars within 1,000 feet. In the future, this could become autonomous emergency braking, which uses sensors like camera or radar that detect an imminent threat, and the car brakes itself. On-board sensors and V2V communication will provide redundancy to make sure the information is correct.
And what sorts of applications use vehicle-to-infrastructure communication?
Today, there are not many V2I projects. Many of the applications use signal phasing and timing. Imagine if you’re coming close to an intersection and the traffic signal phasing and timing are sent to you in advance. Not only do you see the current state of the light, you know when it will change. So you can use that for what we call eco-driving purposes.
The second -- and probably longer term, but certainly immediately doable application -- is adaptive traffic signal control. So imagine a traffic signal, collecting information from various directions. By looking at how far away a car is, it can figure out the queue length at the intersection. You should be able to figure out the traffic flow and change the balance of the red and green signals for all of the directions to help move traffic more efficiently.
How hard is it to install the roadside units that will be collecting the information from cars?
In most big cities, the important intersections are already wired and powered. They have a traffic control cabinet, and the phasing and timing can be controlled from a traffic control center. We already have the communication network and the power necessary, so all you need to do is add wireless communications. DSCR is nothing but a Wi-Fi -- it is a special standard, it is a little bit different, but fundamentally it is a Wi-Fi. So to hook up important intersections today with communications and power, shouldn’t cost more than $2,000 to $3,000 per intersection.
How does a locality decide where to put these units?
People have to want to solve a problem, typically congestion. Collecting data is not the point, using the data is the point. An adaptive traffic signal is one example, but you can also use it to figure out traffic flow.
Right now, we’re not at the point where we’re controlling the signals (in Ann Arbor), but we have a lot of information about the traffic flow and speed of the intersections.
What insight do you get from this?
First, it gives us information on the current state and when and where problems are.
We all know that signal phasing should be different for rush hour and non-rush hour. But most of the traffic signals are not programed optimally. Teams are sent out to measure traffic on one day and that becomes a "normal" day.
Cameras can add a layer of adaptability, but they’re still not as accurate as DSRC. With DSRC you can hear the vehicle position and velocity very accurately. You could use this information to build an adaptive model to react to the current conditions rather than the calibrated condition.
Tell me more about the adaptive signals in Ann Arbor.
Unfortunately, we’re not providing real-time adjustments yet. It certainly is the main concern in any city to do no harm. So the city is being very conservative; officials want us to show more proof that this will do no harm, and, better yet, improve conditions. We have done a lot of simulations that show adaptive signaling would make a significant improvement, but we probably have more convincing to do.
How significant is “significant improvement”?
Even when we do the simulation it is a forecast; it’s not deterministic. Sometimes it shows an improvement of about 2 percent, other times it is as high as 20 percent.
What data are you collecting with the roadside units?
Basically, the most important things are position, velocity and direction of vehicles. Those can provide us with speed, flow and queue length at every intersection.
How much of the data are you collecting? Is it something that a typical DOT can handle?
It depends on your purpose. Let’s say I’m New York City, and I want to know the traffic dynamics and I want to collect year round, then I would save everything.
However, in the real world, you wouldn’t save the data that much. Really, what happened yesterday is history. You save data only for the purpose of research, that’s its only long-term value. So I don’t think it makes sense to save the majority of the data. But, again, if I’m trying to understand traffic in winter vs. summer, how a festival or baseball game affects traffic, then I might save some data for benchmarking and research.
Many cities are standing up smart city and smart transit projects. How do those projects relate to the connected vehicle and DSRC technologies?
The most critical things for the future of smart cities and the internet-of-things projects are data sources and what you can do; in other words, sensors and actuators. The more sensors I have, the more information I have, the more I know the true picture of anything -- urban dynamics, transportation, anything people try to understand. The No. 1 challenge to understanding those things is inadequate data sources.
No. 2 would be: What can you do with the sensor data? Right now, you can call someone on the phone and they’ll do something for you. In the future, it would be nice to be able to directly access the actuators.
The people investing in smart city and infrastructure are adding to sensors and actuators, so certainly we will leverage everything.
Are there any specific applications for DSRC within smart city projects?
Certainly, I think it is important to remember, government focuses on safety as the justification for requiring such a communication device. Safety is the No.1 priority.
One possibility: DSRC can be viewed as an electronic license plate. So today we use a license plate, tomorrow we can use DSRC, and we no longer need a metal plate. The electronic license plate can also be used for electronic toll collection. Right now, toll collection is very fragmented because states and cities have their own systems, but it is reasonable to expect DSRC to provide an ID for the car that can be used to control parking, toll collection and other things.