Whenever we hear a speech from a politician, policy maker, or auto executive extolling the virtues of the self-driving car, it's usually in reference to safety. Little wonder, considering that roughly 40,000 people died on US roads in 2016 (which is a marked uptick from the year before). Humans are not universally good drivers, and many have paid with their lives over time. But there are other benefits to self-driving vehicles, we're told. With a degree of coordination—between vehicles, and with traffic infrastructure—traffic chaos should theoretically be banished, and less congestion means fewer pollutants. Sunshine and roses for everyone!
We're still a long way from that point, however. While the first (geofenced) level 4 autonomous vehicles should begin to appear on some streets around 2020 or 2021, it will be several decades before we get to the point where every car on your commute is self-driving. For now, Clemson researcher Ali Reza Fayazi has provided a tantalizing glimpse at that future, a proof-of-concept study showing that a fully autonomous four-way traffic intersection is a hundred times more efficient at letting traffic flow than the intersections you and I currently navigate. Because cars don't sit idling at the lights, Fayazi calculated it would also deliver a 19 percent fuel saving.
Fayazi designed an intersection controller for a four-way junction that tracks vehicles and then uses an algorithm to control their speeds such that they can all pass safely through the junction with as few coming to a halt as possible. What makes the study particularly interesting is that Fayazi demonstrated it by interspersing his own physical car among the simulated traffic—the first use of a vehicle-in-the-loop simulator for this kind of problem. (Ars has previously tested a vehicle-in-the-loop simulator that demonstrated a pedestrian collision alert system without endangering any actual pedestrians.)
Fayazi drove his real car at the International Transportation Innovation Center in Greenville, South Carolina, where a geofenced area was set up to use as the simulated intersection. Using GPS sensors, his car was just as visible to the intersection controller as the virtual autonomous vehicles that were also populating its memory banks. Ideally, Fayazi says he'd like to have tested it with an autonomous vehicle, but they are hard to come by, particularly in South Carolina. Instead, the intersection controller directly governed his speed in the study (as it did with the simulated vehicles), and this controller sent him a speed to maintain in order to safely cross the junction.
Over the course of an hour, the intelligent intersection only required 11 vehicles to come to a complete halt. By contrast, when the simulation was run with a traffic light instead, more than 1,100 vehicles had to stop at the junction over the course of an hour.
Unfortunately, it's going to be a long time before the rest of us will see that kind of benefit. As you might imagine, it only works when every car that navigates the intersection is being controlled by the system, so this setup won't be much help during transition years that will see a mix of human-driven and autonomous vehicles sharing our streets. There's also the matter of mixing in foot traffic, but Fayazi says his next goal is to make this research applicable to a mixed traffic environment, something we could see somewhat sooner as the smart cities movement grows.
Listing image by Shinichi Higashi