Does pressing the button at pedestrian crossings actually help you cross faster?

Waste of time, mate: London, 1932. Image: Getty.

According to an American study, people spend around 1.6bn hours each year standing idly at the roadside, at the cost of $2.6Bn to the American economy. With all this waiting around, it’s only natural to question whether pushing the “walk” button will help us get to our destination sooner.

To answer this question, we need to understand how the traffic lights work. Strict rules are applied within traffic control hardware to decrease the risk of collisions. For example, minimum times are set between one green light and the next, to ensure that vehicles can clear the junction safely.

While these timings are very important, they can place constraints on the operational efficiency of the junction. If you have ever driven through a city in the early hours of the morning, you’ll know exactly what this means. Despite there being practically no traffic on the road, you will still find yourself frequently stopping at red lights and waiting what can seem like an age for the lights to go green again.

A sign of frustration. Image: lanier67/Flickr/creative commons.

Transport authorities recognise that delay is bad for all users. Idling vehicles contribute to air pollution, and making pedestrians wait does nothing to help government targets to increase the number of trips made on foot. Some towns and cities, such as Drachten in the Netherlands, are even experimenting by removing traffic lights, to improve traffic flow. But in most places, the approach is to ensure traffic lights respond to the demands of those present, within the shortest time possible.


Meeting demand

For a simple pedestrian crossing, located away from a junction, the approach for dealing with pedestrian and traffic demands is simple. Press the button, and the green man or light will appear in due course. How long you wait is a function of how long ago the crossing was last activated, the volume of approaching traffic and the policy of the transport authority.

Many authorities now prioritise pedestrians, meaning that, provided a certain time has elapsed since the last demand for the crossing, the green man will appear almost immediately. If the button is not pressed, traffic will simply continue to flow indefinitely.

At an intersection, the situation depends on the design of the junction and the country you are in. In the UK and Ireland, most urban junctions with simple layouts operate on an “all stop” principle. In this case, traffic on all approaches to the junction is brought to a standstill to allow pedestrians to cross. Like the basic pedestrian crossing, someone must have pressed the button, otherwise the green man will be skipped to reduce delays.

But there is a second junction type, which includes what are known as “parallel” or “walk-with-traffic” pedestrian crossings. In the UK and Ireland, this is achieved on more complex junctions through clever separation of traffic lanes and turning movements, allowing pedestrians to cross while traffic continues to flow.

Crossing in harmony. Image: Rthakrar/Flickr/creative commons.

In continental Europe and cities such as New York, and in other parts of the world, different traffic rules apply, meaning drivers must give way to pedestrians when turning. This makes it easy to implement parallel pedestrian crossings, on even the most basic junctions.

For these junction types, as the pedestrian demands are served at the same time as traffic, in most cases the green man will usually appear regardless of whether the button has been pressed. The only time the button may need to be pushed is during periods of very low traffic volumes, or where the pedestrian crossing – if unused – would inhibit the efficiency of the junction.

At all crossings though, the button only ever needs to be pushed once. Due to the operational rules, pressing it many times or holding it in will not make the green man appear any sooner - even if it may seem that way when you’re in a rush.

To wait or not to wait?

Faced with the prospect of a stand off with the dreaded red man, the impatient pedestrian has a couple of options. Due to the absence of jaywalking laws, many Britons choose simply to cross the road anyway (hopefully only when it is safe to do so). But in places such as Germany, it is the law and the cultural norm to wait for the green man, regardless of traffic - or indeed the lack of it.

With all this waiting around, it is perhaps unsurprising that the ever-pragmatic Germans have come up with a way of killing time, through the installation of push-buttons featuring miniature video games at certain locations.

The ConversationSo the next time you find yourself waiting at a crossing, perhaps rather than fuming at the delay, try to think of ways to make the most of it. But don’t forget to press the button – just in case.

Richard Llewellyn, Lecturer in Transportation Engineering, Edinburgh Napier University.

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

 
 
 
 

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.