Should we remove all the traffic lights from our city centres?

The old enemy. Image: Getty.

They’re a ubiquitous presence in every urban landscape. They’ve launched a million student parties (red for coupled up, yellow for potentially available, green for guaranteed regret). And many traffic engineers believe that they are vital for maintaining safer roads, too.

But the popularity of the humble traffic light is starting to slide. They’re been linked to road rage, explosions, humankind’s declining sense of social responsibility, and, in recent years, have even started to turn on each other. So is it time to get rid of traffic lights altogether?

The first, gas-fuelled, traffic light was installed outside the Houses of Parliament in London in 1868. Within a month, it had dramatically uninstalled itself by exploding.  

Over 40 years later, a policeman called Lester Wire (yes, that’s his real name) developed the first electric traffic light in Salt Lake City, Utah. Wire’s invention must have sparked something (arf) because designers around the United States were soon clamouring to get in on the action (there was, apparently, not much fun to be had in the early 20th century). Soon cities across the US were bedecked with traffic lights that flashed, beeped, whistled and generally worked hard to raise the nation’s blood pressure.

Obviously, it’s not possible to blame all road rage on traffic lights (at least, not as long as Scott Mills is on Radio 1). But there is enough of a link that, in 2008, researchers developed “smart traffic lights”. This invention was prompted by studies which had found that incessant braking and accelerating caused a spike in road rage. Abrupt changes in speed, and uncertainty over when the lights would change, infuriated drivers and led to dangerous driving.


With this in mind, American and Romanian researchers developed talking traffic lights: a set of lights which would announce to drivers if they should be moving slower or braking. It’s a bit like having a backseat driver, but one which is peering into the front of your car, and is also a robot.

While their effectiveness is still up for debate, one city was impressed enough to install talking traffic lights in 20 locations around in 2015. Newcastle University collaborated teamed up with the city council to start trialling the lights. As Phil Blythe, the university’s professor of intelligent transport systems, explained to the International Business Times: "The system might advise a driver that if they travel at 24mph they will get the next four sets of traffic lights on green."

In other words, we’ve created a set of traffic lights to help us avoid traffic lights.

Legendary traffic engineer Hans Monderman once said: “The trouble with traffic engineers is that when there's a problem with a road, they always try to add something. To my mind, it's much better to remove things.” He believed that people are losing their capacity for socially responsible behaviour and that light-free roads were the answer.

By making road users more responsible for their driving decisions, Monderman hoped to reduce the modern driver’s dependency on the accelerator. Forcing drivers to slow down in order to examine their surroundings, rather than just because a light on a pole ordered them to, would, he believed, help create safer and more harmonious roads.

Monderman’s influence can be seen at the bottom of my road in Amsterdam, where an intersection used by car drivers, vans, lorries, cyclists and pedestrians is completely light-free.

The first few times I tried to use this crossing I ended up getting off my bike and pushing it across. The road was too big, and there were too many lanes (eight; 12 if you count the bike lanes) to keep track off. This was a built-up, inner-city neighbourhood: giving cars free reign to barrel through unchecked was surely low-budget population control, if not an outright declaration of war.

My neighbourhood, I later realized, is covered in these naked intersections. It took a few weeks for me to feel comfortable with all this nudity. It took another six months before I realised how much they’ve improved my behaviour as a cyclist.

I normally race towards green traffic lights, desperate to avoid facing down a red-eyed cyclops. If anyone gets in my way, either they or I will end up picking gravel out of our vital organs. But these traffic-light-free intersections make me slow down, look around, and clock the elderly man attempting to cross the road while clutching a priceless Ming vase. They make me a better cyclist and turn my neighbours into more cautious drivers.

So, traffic lights. They encourage road rage; they allow drivers to become less responsible in their driving; and hackers could one day take control of the things. Why do we need them again?

 
 
 
 

Just like teenagers, self-driving cars need practice to really learn to drive

A self-driving car, of unknown level of education. Image: Grendelkhan/Flickr/creative commons.

What do self-driving cars and teenage drivers have in common?

Experience. Or, more accurately, a lack of experience.

Teenage drivers – novice drivers of any age, actually – begin with little knowledge of how to actually operate a car’s controls, and how to handle various quirks of the rules of the road. In North America, their first step in learning typically consists of fundamental instruction conveyed by a teacher. With classroom education, novice drivers are, in effect, programmed with knowledge of traffic laws and other basics. They then learn to operate a motor vehicle by applying that programming and progressively encountering a vast range of possibilities on actual roadways. Along the way, feedback they receive – from others in the vehicle as well as the actual experience of driving – helps them determine how best to react and function safely.

The same is true for autonomous vehicles. They are first programmed with basic knowledge. Red means stop; green means go, and so on. Then, through a form of artificial intelligence known as machine learning, self-driving autos draw from both accumulated experiences and continual feedback to detect patterns, adapt to circumstances, make decisions and improve performance.

For both humans and machines, more driving will ideally lead to better driving. And in each case, establishing mastery takes a long time. Especially as each learns to address the unique situations that are hard to anticipate without experience – a falling tree, a flash flood, a ball bouncing into the street, or some other sudden event. Testing, in both controlled and actual environments, is critical to building know-how. The more miles that driverless cars travel, the more quickly their safety improves. And improved safety performance will influence public acceptance of self-driving car deployment – an area in which I specialise.

Starting with basic skills

Experience, of course, must be built upon a foundation of rudimentary abilities – starting with vision. Meeting that essential requirement is straightforward for most humans, even those who may require the aid of glasses or contact lenses. For driverless cars, however, the ability to see is an immensely complex process involving multiple sensors and other technological elements:

  • radar, which uses radio waves to measure distances between the car and obstacles around it;
  • LIDAR, which uses laser sensors to build a 360-degree image of the car’s surroundings;
  • cameras, to detect people, lights, signs and other objects;
  • satellites, to enable GPS, global positioning systems that can pinpoint locations;
  • digital maps, which help to determine and modify routes the car will take;
  • a computer, which processes all the information, recognising objects, analysing the driving situation and determining actions based on what the car sees.

How a driverless car ‘sees’ the road.

All of these elements work together to help the car know where it is at all times, and where everything else is in relation to it. Despite the precision of these systems, however, they’re not perfect. The computer can know which pictures and sensory inputs deserve its attention, and how to correctly respond, but experience only comes from traveling a lot of miles.

The learning that is occurring by autonomous cars currently being tested on public roads feeds back into central systems that make all of a company’s cars better drivers. But even adding up all the on-road miles currently being driven by all autonomous vehicles in the U.S. doesn’t get close to the number of miles driven by humans every single day.

Dangerous after dark

Seeing at night is more challenging than during the daytime – for self-driving cars as well as for human drivers. Contrast is reduced in dark conditions, and objects – whether animate or inanimate – are more difficult to distinguish from their surroundings. In that regard, a human’s eyes and a driverless car’s cameras suffer the same impairment – unlike radar and LIDAR, which don’t need sunlight, streetlights or other lighting.

This was a factor in March in Arizona, when a pedestrian pushing her bicycle across the street at night was struck and killed by a self-driving Uber vehicle. Emergency braking, disabled at the time of the crash, was one issue. The car’s sensors were another issue, having identified the pedestrian as a vehicle first, and then as a bicycle. That’s an important distinction, because a self-driving car’s judgments and actions rely upon accurate identifications. For instance, it would expect another vehicle to move more quickly out of its path than a person walking.


Try and try again

To become better drivers, self-driving cars need not only more and better technological tools, but also something far more fundamental: practice. Just like human drivers, robot drivers won’t get better at dealing with darkness, fog and slippery road conditions without experience.

Testing on controlled roads is a first step to broad deployment of driverless vehicles on public streets. The Texas Automated Vehicle Proving Grounds Partnership, involving the Texas A&M Transportation Institute, University of Texas at Austin, and Southwest Research Institute in San Antonio, Texas, operates a group of closed-course test sites.

Self-driving cars also need to experience real-world conditions, so the Partnership includes seven urban regions in Texas where equipment can be tested on public roads. And, in a separate venture in July, self-driving startup Drive.ai began testing its own vehicles on limited routes in Frisco, north of Dallas.

These testing efforts are essential to ensuring that self-driving technologies are as foolproof as possible before their widespread introduction on public roadways. In other words, the technology needs time to learn. Think of it as driver education for driverless cars.

People learn by doing, and they learn best by doing repeatedly. Whether the pursuit involves a musical instrument, an athletic activity or operating a motor vehicle, individuals build proficiency through practice.

The ConversationSelf-driving cars, as researchers are finding, are no different from teens who need to build up experience before becoming reliably safe drivers. But at least the cars won’t have to learn every single thing for themselves – instead, they’ll talk to each other and share a pool of experience.

Johanna Zmud, Senior Research Scientist, Texas A&M Transportation Institute, Texas A&M University .

This article was originally published on The Conversation. Read the original article.