Cats and dogs and Pokémon and ball pools: The eight joyful trains of Japan

Okay, it may not look like much, but... the exterior of the Genbi Shinkansen art experience. Image: ©Mika Ninagawa, used courtesy of Tomio Koyama Gallery.

If you’re on this website, you’ll likely agree with the statement: trains are good. We like trains. Trains are marvellous.

But in Britain our idea of a good train is “runs on time, doesn’t smell of wee, possibly has a spare seat”. Our national rail ambition has been battered by years of this crap: the most exciting we can hope for is to catch sight of the Orient Express as it flashes through a station, or a ride on the Settle to Carlisle railway.

Yet in Japan, there are trains dedicated to art and sake and Pokemon. There’s a train with a ball pool, for Christ’s sake.

These trains aren’t usually part of the ‘real’ timetable (that is, they don’t show up in the regular searches), and sometimes only run on specific days, they do still run proper routes. The Tohoku Emotion, for instance (all about dining; one car is an open kitchen) runs between Hachinohe and Kuji, adding a direct train between those cities in an otherwise annoying two hour gap.


Cost is, of course, another issue. It’s not possible to book many of these trains outside Japan so prices are tricky to come by, and some of the dining packages on offer will obviously involve laying down some hefty yen.

That said, the Kawasemi Yamasemi, an exquisitely decorated train that runs three times every day direct between Kumamoto and Hitoyoshi in central Kyushu, costs about the same as travelling between the two on the bullet train (it’s faster too, because it’s direct). And I’m happy to bet the farm that any of these trains will cost a damn sight less than Japan’s newest, shiniest novelty train – and probably be more fun.

So without further ado, here are some of the best – and this really is what they’re called – Joyful Trains in Japan.

Pokémon with YOU

Yes, there really is a Pokémon train. Introduced in Tohoku to cheer up – and raise money for – the region’s children after the 2011 earthquake and tsunami, the service runs between Ichinoseki and Kesennuma stations, and if Niantic hasn’t worked out a way to put special Pokémon Go characters at each station, it’s missing a trick. There’s a playroom with big Snorlax cushions, the Drilbur Tunnel and real life Poké balls. And, as far as we can tell, a seat costs less than a fiver.

Oh, and because it’s run by JR East, you can do a Google Street View walkthrough of the whole train, which are available for many of the company’s Joyful Trains. Japan. Is. Awesome.

Image: Google Street View.

Tama-Den

If cute character-themed trains are your thing, then you should also check out the Tama-Den which runs on the Wakayama Electric Railway’s Kishigawa line. Tama, you may recall, was a calico cat who became feted as a stationmaster, and elevated into a goddess when she died in 2015. (Her replacement, Tama II, works a five day week at Kishi station.) The Tama-Den is covered in drawings of her. And you thought your cat was spoiled.

Meow? Image: as365n2/Flickr/creative commons.

The same company also runs the Omo-den, which is all about toys and has cash-guzzling capsule toy vending machines on board.

Aso Boy!

Where there’s a cat train, there must also be a dog. Aso Boy! usually takes you past the caldera of Mount Aso, the largest active volcano in Japan, but since the Kumamoto earthquake the route is altered.

 But even with the lack of its main scenic draw, this is still a top train because it features the cutest of all Japan’s regional mascots. Kuro is JR Kyushu’s yuru-chara and the damnably adorable dog gets everywhere. It’s one-up on the Tama-Den because you can buy Kuro-themed food and souvenirs, and this is the train with the ball pool.

The balls are wooden though. Ouch.

On board Aso Boy! Image: Jill Chen/Flickr/creative commons.

Genbi Shinkansen

The bullet train is cool enough, but this one is decorated inside and out with the work of eight modern artists. Running between Niigata and Echigo-Yuzawa, the Genbi Shinkansen reckons it’s the world’s fastest art experience. With a journey time of just under an hour, works range from standard wall-mounted paintings to art that’s literally part of the furniture.

Images: ©Mika Ninagawa, used courtesy of Tomio Koyama Gallery.

SL Ginga

Not only is this train hauled by a steam locomotive, it has a freaking planetarium on board. It’s inspired by children’s author Kenji Miyazawa’s book Night on the Galactic Railroad which is set in the early 20th century, and the decor is meant to echo that era. There are galleries devoted to Miyazawa’s life, and the train runs between Hanamaki – where he was from – and Kamaishi.

Image: Google Street View.

FruiTea Fukushima

The whole of Fukushima province has been tainted by association with its namesake nuclear power plant, which is deeply unfair as it’s a gorgeous part of the country.

To drum up tourism, the FruiTea train went into service a couple of years ago on the standard line connecting Koriyama to Aizu-Wakamatsu, a castle-and-samurai town. There are several Joyful Trains dedicated to eating and drinking, but this one deserves a mention because its locally produced fruit snacks and drinks deserve wider recognition. As does the area.

Here’s your Google Street View walkthrough:

Image: Google Street View.

Shu*Kura

There are three Shu*Kura trains, all departing from Joetsumyoko but with different destinations. This is another train dedicated to eating and, well... drinking.

Niigata Prefecture claims to brew the finest sake in the world, and this three car service showcases the best of them. It also has live music and snacks, but the point here is that you can stand at a sake cask-themed bar and get tiddly without anyone judging you, like they would for that M&S prosecco.

And check out the lights on that thing.

Image: Google Street View.

Toreiyu Tsubasa

This is the train to catch if you want to go full Japan. Most of the cars don’t have seats, they have tatami mats and low tables instead, billed as a ‘conversation space’.

There’s another tatami car designed as more of a lounge for people after they’ve used the footbath. Yes, you did read that correctly. A footbath. You’re not going to want your shoes with all this tatami anyway, and it’s a unique way to view the scenery between Fukushima and Shinjo.

Image: Google Street View.

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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.