When you put a human driver behind the wheel, they will use primarily their eyes to navigate. Both to stay on the road and to use any navigation aids, such as maps and digital navigation assistants. For self-driving cars, tackling the latter is relatively easy, as the system would use the same information in a similar way: when to to change lanes, and when to take a left or right. The former task is a lot harder, with situational awareness even a challenge for human drivers.
In order to maintain this awareness, self-driving and driver-assistance systems use a combination of cameras, LIDAR, and other sensors. These can track stationary and moving objects and keep track of the lines and edges of the road. This allows the car to precisely follow the road and, at least in theory, not run into obstacles or other vehicles. But if the weather gets bad enough, such as when the road is covered with snow, these systems can have trouble coping.
Looking for ways to improve the performance of autonomous driving systems in poor visibility, engineers are currently experimenting with ground-penetrating radar. While it’s likely to be awhile before we start to see this hardware on production vehicles, the concept already shows promise. It turns out that if you can’t see whats on the road ahead of you, looking underneath it might be the next best thing. Continue reading “Navigating Self-Driving Cars By Looking At What’s Underneath The Road”
In a recent study by a team of researchers at MIT, self driving cars are being programmed to identify the social personalities of other drivers in an effort to predict their future actions and drive safer on roads.
It’s already been made evident that autonomous vehicles lack social awareness. Drivers around a car are regarded as obstacles rather than human beings, which can hinder the automata’s ability to identify motivations and intentions, potential signifiers to future actions. Because of this, self-driving cars often cause bottlenecks at four-way stops and other intersections, perhaps explaining why the majority of traffic accidents involve them getting rear-ended by impatient drivers.
The research taps into social value orientation, a concept from social psychology that classifies a person from selfish (“egoistic”) to altruistic and cooperative (“prosocial”). The system uses this classification to create real-time driving trajectories for other cars based on a small snippet of their motion. For instance, cars that merge more often are deemed as more competitive than other cars.
When testing the algorithms on tasks involving merging lanes and making unprotected left turns, the behavioral predictions were shown to improve by a factor of 25%. In a left-turn simulation, the automata was able to wait until the approaching car had a more prosocial driver.
Even outside of self-driving cars, the research could help human drivers predict the actions of other drivers around them.
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At the turn of the 21st century, it became pretty clear that even our cars wouldn’t escape the Digital Revolution. Years before anyone even uttered the term “smartphone”, it seemed obvious that automobiles would not only become increasingly computer-laden, but they’d need a way to communicate with each other and the world around them. After all, the potential gains would be enormous. Imagine if all the cars on the road could tell what their peers were doing?
Forget about rear-end collisions; a car slamming on the brakes would broadcast its intention to stop and trigger a response in the vehicle behind it before the human occupants even realized what was happening. On the highway, vehicles could synchronize their cruise control systems, creating “flocks” of cars that moved in unison and maintained a safe distance from each other. You’d never need to stop to pay a toll, as your vehicle’s computer would communicate with the toll booth and deduct the money directly from your bank account. All of this, and more, would one day be possible. But only if a special low-latency vehicle to vehicle communication protocol could be developed, and only if it was mandated that all new cars integrate the technology.
Except of course, that never happened. While modern cars are brimming with sensors and computing power just as predicted, they operate in isolation from the other vehicles on the road. Despite this, a well-equipped car rolling off the lot today is capable of all the tricks promised to us by car magazines circa 1998, and some that even the most breathless of publications would have considered too fantastic to publish. Faced with the challenge of building increasingly “smart” vehicles, manufacturers developed their own individual approaches that don’t rely on an omnipresent vehicle to vehicle communication network. The automotive industry has embraced technology like radar, LiDAR, and computer vision, things which back in the 1990s would have been tantamount to saying cars in the future would avoid traffic jams by simply flying over them.
In light of all these advancements, you might be surprised to find that the seemingly antiquated concept of vehicle to vehicle communication originally proposed decades ago hasn’t gone the way of the cassette tape. There’s still a push to implement Dedicated Short-Range Communications (DSRC), a WiFi-derived protocol designed specifically for automotive applications which at this point has been a work in progress for over 20 years. Supporters believe DSRC still holds promise for reducing accidents, but opponents believe it’s a technology which has been superseded by more capable systems. To complicate matters, a valuable section of the radio spectrum reserved for DSRC by the Federal Communications Commission all the way back in 1999 still remains all but unused. So what exactly does DSRC offer, and do we really still need it as we approach the era of “self-driving” cars?
Continue reading “When Will Our Cars Finally Speak The Same Language? DSRC For Vehicles”
In 1899, you might have been forgiven for thinking the automobile was only a rich-man’s toy. A horseless carriage was for flat garden pathways. The auto was far less reliable than a horse. This was new technology, and rich people are always into their gadgets, but the automobile is a technology that isn’t going to go anywhere. The roads are too terrible, they don’t have the range of a horse, and the world just isn’t set up for mechanized machines rolling everywhere.
This changed. It changed very quickly. By 1920, cars had taken over. Industrialized cities were no longer in the shadow of a mountain of horse manure. A highway, built specifically for automobiles, stretched from New York City to San Francisco. The age of the automobile had come.
And here we are today, in the same situation, with a technology as revolutionary as the automobile. People say self-driving cars are toys for rich people. Teslas on the road aren’t for the common man because the economy model costs fifty thousand dollars. They only work on highways anyway. The reliability just isn’t there for level-5 automation. You’ll never have a self-driving car that can drive over mountain roads in the snow, or navigate a ball bouncing into the street of a residential neighborhood chased by a child. But history proves time and time again that people are wrong. Self-driving cars are the future, and the world will be unrecognizable in thirty years. There’s only one problem: we’re not calling them the right thing. Self-driving cars should be called ‘cryptocybers’.
Continue reading “The Problem With Self-Driving Cars: The Name”
In one bad week in March, two people were indirectly killed by automated driving systems. A Tesla vehicle drove into a barrier, killing its driver, and an Uber vehicle hit and killed a pedestrian crossing the street. The National Transportation Safety Board’s preliminary reports on both accidents came out recently, and these bring us as close as we’re going to get to a definitive view of what actually happened. What can we learn from these two crashes?
There is one outstanding factor that makes these two crashes look different on the surface: Tesla’s algorithm misidentified a lane split and actively accelerated into the barrier, while the Uber system eventually correctly identified the cyclist crossing the street and probably had time to stop, but it was disabled. You might say that if the Tesla driver died from trusting the system too much, the Uber fatality arose from trusting the system too little.
But you’d be wrong. The forward-facing radar in the Tesla should have prevented the accident by seeing the barrier and slamming on the brakes, but the Tesla algorithm places more weight on the cameras than the radar. Why? For exactly the same reason that the Uber emergency-braking system was turned off: there are “too many” false positives and the result is that far too often the cars brake needlessly under normal driving circumstances.
The crux of the self-driving at the moment is precisely figuring out when to slam on the brakes and when not. Brake too often, and the passengers are annoyed or the car gets rear-ended. Brake too infrequently, and the consequences can be worse. Indeed, this is the central problem of autonomous vehicle safety, and neither Tesla nor Uber have it figured out yet.
Continue reading “Fatalities Vs False Positives: The Lessons From The Tesla And Uber Crashes”
Self-driving cars are starting to pop up everywhere as companies slowly begin to test and improve them for the commercial market. Heck, Google’s self-driving car actually has its very own driver’s license in Nevada! There have been minimal accidents, and most of the time, they say it’s not the autonomous cars’ fault. But when autonomous cars are widespread — there will still be accidents — it’s inevitable. And what will happen when your car has to decide whether to save you, or a crowd of people? Ever think about that before?
It’s an extremely valid concern, and raises a huge ethical issue. In the rare circumstance that the car has to choose the “best” outcome — what will determine that? Reducing the loss of life? Even if it means crashing into a wall, mortally injuring you, the driver? Maybe car manufacturers will finally have to make ejection seats a standard feature!
Continue reading “The Ethics Of Self-Driving Cars Making Deadly Decisions”