“We talk for hours and hours about the sweet and the sour …” – Jenny’s favorite Ed Sheeran song suddenly pops into her head, but there’s no time for hours of chatting right now. With a glance at the time – it’s just before 9 a.m. – she has just put down her mobile phone a second ago after hastily ending a call with her friend Kerstin with the words “You’re a sweetheart!” Because, from now on, every minute counts.
Who expects to be invited to a meeting with Ed Sheeran in Hamburg on a Saturday morning, in Jenny's case right between her shower and breakfast? What a start to a weekend that had up until then she had expected to be pretty boring! Okay, “meeting” is perhaps a bit of an exaggeration. But a live concert by a star whose music has already given her and her friend many hours of joy, that’s quite something. Jenny had known for weeks that Kerstin's sister had managed to get two tickets last summer. That alone was a stroke of luck, and you could only feel good for her. Almost every one of the British superstar’s few German concerts had sold out within minutes.
Now Kerstin was looking for a replacement for her sister of all people – “... that’s why I’m calling – she’s sick, with a 102 degree fever, so she can’t possibly...” – Jenny almost felt guilty. But with a quick look at the time – “The train won’t be quite on time, it only leaves at five past 10 from the main station” – she made a quick calculation: “I can make it.” Jenny is happy that the train is late today of all days. She's actually a punctual person. But the DB Navigator app told the two women that she has a bit of extra time today. Jenny regularly travels by train and has been annoyed sometimes when a train has arrived too late. Especially when she was informed about the delay on the platform with only vague information like “in a few minutes.” She gives brief thanks for the fact that her wish for a possible delay and timely information about it has been granted, thanks to Deutsche Bahn’s new forecasting machine. A closer look at the DB Navigator shows her that her friend was right. Instead of departing on schedule at 9:46 a.m., the Intercity train will leave Cologne 19 minutes later. If she hurries now, there might even be time for a quick breakfast at the station.
Jenny calculates that 20 minutes will be enough for a lighting quick check in the bathroom mirror, a quick change of clothes and packing the essentials for the night. Unlike her friend who lives in downtown Cologne, Jenny lives in the suburb of Brühl. It’s a good 12 miles from there to the city center, depending on the route. Taking the RB26 train to the central station, where Kerstin would wait for her, could work. But what if that train is also delayed, for example due to a disturbance on the track? Jenny decides against it.
“Leave and get in a taxi” – she thinks that following the advice from Ed Sheeran’s “Shape of you,” seems the better idea today. “9:20 a.m., Parkstrasse 17,” the taxi office confirms that a driver will pick Jenny up on time. And when she steps out of the elevator, Jenny can already see the taxi waiting at the front door. She tells the driver her destination and takes a seat in the back – she looks at the app again. And indeed – should the taxi ride be delayed on the motorway ring to the A555 in the direction of the city center, this still shouldn’t be a cause for panic. But a quick check of the updated information from the forecasting machine shows: The IC 2310 on its way to the North Sea island of Sylt will now leave Cologne Central Station at 10:03 a.m. Nevertheless: That’s still 17 minutes later than scheduled, Jenny calculates and immediately informs her friend via WhatsApp. And she answers immediately: “Great! If it stays that way and you’re on time, there’ll even be enough time for an Iced Latte ”. At the thought, Jenny immediately thinks of Ed Sheeran’s “Cold Coffee.”
“Tell me if I’m wrong, tell me if I’m right ”, it says in the song, but she hasn’t needed these kinds of hurried prayers for a while when travelling by train. That’s because for months, the forecasting machine has been making real time and downtotheminute forecasts of the arrival and departure times of all Deutsche Bahn longdistance trains. Jenny recently heard something about a “learning system” on the radio. She always wanted to read about it and plans to do so later (see box on p. 39). As expected, her taxi driver knows the way to Cologne Central Station even without a navigation device. But when his passenger asks him when they’ll reach their destination, the man at the wheel just taps his dashboard display: “There’s a little traffic jam at the turnoff into to the city center. But we’ll arrive at 9:45.”
The driver is right. At a quarter to ten Jenny hands over the taxi fare and tip, gets out of the car and sees Kerstin waving to her in front of the station. Her friend approaches her with the words: “Do you know what’s the best thing? There’s another small correction. But the departure time of our IC is now one minute past 10. That’s cool twice over!” “What do you mean?” “I just see it that way,” she explains her view of things to Jenny: “A delay is a delay. But if you as a passenger are informed in time, you can use the time, make the best of it and don’t have to rush to the platform to find out that the rush was for nothing.” And Kerstin immediately calculated what that means for the two women right at that moment: “As a result, we have enough time not just for a coffee, but also for a croissant.”
“My belly’s sick to its stomach …,” Ed Sheeran sings in the ballad “Miss You.” And that would have been exactly Jenny’s feeling previously, so that she wouldn’t have been able to eat a bite in this situation. The fear of missing the train – at least this particular one – would have hit her too hard in the stomach. But now, the two women are happy, everything is fine. At the café, Kerstin explains their itinerary to her friend in detail. The whole journey without changing trains takes just over four hours. But before the concert she wants to check in at the hotel.
And anyone who really wants to “get closer” to Ed Sheeran at the concert at the race track in Hamburg's Bahrenfeld district, i.e. in the area 11 to 13 yards in front of the stage, should get there early.On their way to platform 4, Kerstin wants to look at the app again, just to be certain. When booking the train tickets for herself and her sister, she had “ticked” via the app that she wanted to be informed automatically about changes in the departure time of “IC 2310.” Her smartphone therefore notifies her of any changes to the timetable both acoustically and visually. But better safe than sorry.
“Give a little time to me or burn...” – well, it’s clear that sums up the way train passengers perceive every minute they wait on the platform as wasted time. The forecasting machine continues to predict “10:01 a.m.” as the final departure time. “We can actually have a quick look in the station pharmacy.” Minutes later the two women climb the last few steps up to the platform and see their Intercity already arriving into the station from the south. Exactly a quarter of an hour late, “... but also somehow on time, down to the last minute,” to the delight of the two women.
Contact: J.Betz@t-systems.com
Rail travelers want to know as precisely as possible when their journey begins, how long it will take and when they will arrive at their destination. But journey and arrival times change constantly, just as if you are driving, depending on the traffic situation. That is why Deutsche Bahn now relies on a forecast automat and on complex analysis of real-time data. T-Systems and Deutsche Bahn use it to forecast the train’s arrival and departure times at stations and to calculate alternative routes for travelers. Peter Schütz, Head of Traveler Information at Deutsche Bahn AG, explains in this interview that data from routes and stations is constantly relayed to the forecast automat. This includes secondary information supplied by the system, such as details of other trains’ delays.
Deutsche Bahn has used Big Data forecasting on all long-distance routes since 2018 and experience gained with long-distance traffic is to be applied to regional traffic forecasting in 2019.
