Five things we already know about Crossrail 2’s Euston-St. Pancras mega-station

Could all this be one station soon? Euston (left), St. Pancras (centre), Kings Cross (right). Image: Google.

Okay, Crossrail hasn’t even finished yet, but there’s no better time to get excited about all things Crossrail 2 than at least 12 years too early.

By far the most impressive sounding of the improved stations it’ll bring is north London’s new, so-called ‘megastation’: Euston St. Pancras. This will involve joining Euston and King’s Cross St. Pancras together as one giant underground station. Some versions of the plans show Euston Square being absorbed into the whole thing, too.

And so, to whet your appetite, here are five (loosely defined) facts about the proposals.

1. It will be the biggest station in London…

At the moment, the south rules, with Waterloo receiving 100m or so entry and exits annually – a number very likely to grow over the coming years.

The proposed Crossrail 2 route.

Fairly impressive, you might think. Not to Euston St. Pancras, which merges two of the busiest train stations in the capital (and, let’s not forget, Euston Square).

Even without considering the capacity increase brought by Crossrail 2 – around 10 per cent, to be precise – a merger of the three stations now would serve a whopping 150m people per year. That’s about 5 per cent of all the passengers on the entire underground network, passing through that station alone.

2. ...so big, in fact, that you might be able to get a train from one end to the other

“This is Euston St. Pancras. The next station is Euston St. Pancras.”

Sure, Bank may be a hellish labyrinth (especially in this never-ending heat) but it’s not quite a 15-minute brisk walk end-to-end. That’s about how long it takes to walk along the Euston Road, from the westernmost proposed entrance to the easternmost entrance of King’s Cross St. Pancras, as it currently stands.

Oh god: an unofficial draft of the 2040 tube map, showing Crossrail 2. Image: Ali Carr.

Just as well then, that Euston St. Pancras may well end up having a tube journey from end to end. Today, both the Victoria line and Bank branch of the Northern line run east from Euston to King’s Cross St. Pancras. If HS2 ends up meaning Euston Square gets in on the action too, that’ll be five different tube lines which will do this. If that’s not the definition of a megastation, I’m not sure what is.

3. Its trains will serve destinations over 1,000 miles apart

Okay, I accept that maybe this is cheating. This isn’t technically a fact about the tube station – although it would be a pretty impressive show of one-upmanship on Crossrail’s Reading-Shenfield record.

It is, however, the distance you’ll be able to travel with just one change in the Euston-King’s Cross-St. Pancras complex. Euston’s Caledonian sleeper can take you up to the capital of the Highlands, Inverness, whilst St. Pancras’s Eurostar service stretches down to Marseilles on the Mediterranean coast in the summer.

Unfortunately, no reliable source could tell me whether Hogwarts is to the north or south of Inverness, so I haven’t been able to account for services departing from Platform 9¾.

4. Euston St. Pancras will finally out-do Liverpool Street for number of lines served

Right now, King’s Cross St. Pancras serves the largest number of lines on the tube network, six. It shares this title with Bank (Central, Northern, Waterloo & City, DLR), if you count Monument (District, Circle). It sort shares it with Liverpool Street (four tube lines, plus Overground and TfL Rail), too.

Thanks to that pesky Crossrail 1, Liverpool Street will soon increase its count to seven – replacing TfL Rail with the proper Elizabeth Line, and gaining a direct link to the Northern line’s Bank branch at Moorgate. But, following a £30bn infrastructure project and three-station merger, Euston St. Pancras will finally leave Liverpool Street in the dust with an unprecedented eight lines – gaining Euston’s Overground coverage and, of course, Crossrail 2.


5. It has a really stupid name

Now, this may sound like an opinion rather than a fact – but hear me out.

King’s Cross is perhaps the most significant station of the three. Firstly, it is the name most associated with that area of London these days, despite St. Pancras’s long history as the rightful title of the area. It thus seems ludicrous to drop it from the name of the station.

Secondly, doing so threatens to reignite a centuries-long rivalry. The original King’s Cross station, home of the Great Northern Railway, used to host its rivals, the Great Midlands Railway, until the latter decided to build the bigger, fancier station just over the road.

Despite the Great Midlands’ best efforts, King’s Cross still stands strong, even beating St. Pancras in passenger numbers. So, let’s not let the TfL naming system glibly allow the neo-gothic flashman of a station finally do in its older, less ostentatious rival.

 

Proposed works in the Euston St. Pancras area. Image: Crossrail 2.

Then what should we end up calling it?

Perhaps we can add another fact to the list with the most convoluted name: Euston Square King’s Cross St. Pancras. Or opt for the subtler Somers Town, the home of all three stations, from the Great Northern-Midlands rivalry until now – and the place shaped most by this monumental project.

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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.