A third Heathrow will mean congestion, pollution and inconvenience. There is another way

A plane comes into land at Heathrow. Image: Getty.

There must be some credible reason why the government would back a plan to extend an overcrowded, polluting airport, entrenching the monopoly of a foreign owner, whilst demolishing historic villages in the process. But I’m struggling to find it.

The M25 is already a traffic jam around Heathrow at most times of the day, yet we’re told almost doubling passenger numbers won’t make matters worse. Some 100m vehicles flow between junctions 14 and 15 of the M25 every year – and we don’t think an extra 50 million passengers out of Heathrow will add to that?

Even before this extra traffic is pushed onto the road we can expect chaos as a new tunnel is dug to take the M25 beneath the new runway, because space is at such a premium.

Congestion, though, is the least of our worries. In the Aussie movie The Castle the Kerrigan family find that their makeshift home, teetering on the edge of Melbourne’s Tullamarine Airport, is threatened with demolition to make room for a new runway. “Tell ‘em they’re dreamin,” was the laconic war cry from Darryl Kerrigan, as the Aussie battlers take their case to the High Court.

Sound familiar?

Now, hundreds of Kerrigan families face a similar threat from Heathrow. The new north-west runway will see their homes and neighbourhood ripped apart. The village of Harmondsworth will be practically tarmacked over, and what remains will be so close to the airport perimeter that life will never be the same again. This parish, so old it’s featured in the Doomsday book, will become history. 

Then there’s the danger to the great crested newt. Don’t get me started on the newts.

Worse still, heaping extra traffic on Heathrow – taking it from 78m to 130m passengers a year – increases its monopoly over other London airports, seeing more profits repatriated back to its Spanish owners.

All in all, this “historic moment for the UK” spells disaster. Yet transport secretary Chris Grayling seems intent on extending the chaos on our railways onto our roads and airports.

The two reasons I have heard in favour of the Heathrow decision are both circular arguments. 

First, we’ve seen a lot of economic growth in the Thames Valley because of its proximity to Heathrow. That’s the claim. I suspect proximity to London is more likely the driving force, but if it’s the airport, then extending Gatwick could have a similar impact on growth to the south of London, rather than adding to congestion along the Thames corridor.


The second argument revolves around the importance of being a hub. Almost a third of passengers at Heathrow transit between flights. The more aircraft land. the more onward flights for passengers to choose from. If we don’t add these choices we’ll lose out to other, competing hubs, like Schiphol in Amsterdam. 

But if the traveller’s ultimate destination is outside the UK, who cares if they don’t fly via Heathrow? Transit passengers might buy a coffee and help keep a toilet cleaner in a job, but they’re also adding to air pollution and noise. Let Schiphol deal with them. The Spanish owners will lose a few quid, but that’s hardly our concern.

The same applies for travellers bound for the UK – do we care where they interconnect, so long as they get here and start spending? And their holiday will get off to a better start if they land practically anywhere in the UK other than Heathrow, with the possible exception of Luton.

Yet there is a plan that would solve the pollution, congestion and competition issues in one fell swoop, if only the government would listen. Alistair Lenczner, from engineering consultancy Expedition, suggests a high speed rail link, offering a 15 minute connection between the two airports. In fact, the proposal goes further, with HS4 Air linking to HS2 to the north and looping south of London to join HS1 in Ashford.  

A quarter hour journey time between the two airports would make transiting flights a possibility. Increasing Gatwick to the size of Heathrow today would mean each airport would compete for airlines, lowering landing rates and offering better value for customers. You’d assume there would be a greater variety of operators and destinations overall, increasing the competitiveness against foreign hubs, if we really see that as an important consideration.

Passengers could park at Gatwick or Heathrow, easing congestion on the M25 rather than adding to it. Businesses that want to be near international links can pay a premium to base themselves near Reading, or choose newly developing business parks from Crawley to Brighton – or at any point along the new HS4 Air route. And 2m people in West London wouldn’t suffer an increase air traffic noise. 

The idea of an extra runway at Heathrow has been on the cards for 30 years or more. In that time we’ve seen road traffic and air pollution go from bad to worse. Is piling on the numbers at one of the world’s busiest airports the best we can do?

If Chris Grayling really thinks the Heathrow extension plan is the most elegant solution for our future air travel demands, someone has to tell him he’s dreamin’.

Phil Dobbie is a freelance journalist, business podcaster and commentator. He presents Saturday nights from 10pm to 1am on LoveSport Radio in London.

 
 
 
 

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.