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Simulación · Minimal City · Germany

Berlin · Central Station, Chancellery and the Spree

Berlin around the Central Station as a living model: people, cars, buses and trains, each with its own destination, with tunnels, water, power and data underneath – and controls that show at once how it all connects.

Trailer

Real are location, streets, buildings, tracks, stops and venues (OpenStreetMap). Traffic, service intervals, residents, jobs and network routes are model assumptions. With your data, the model shows your city and your questions.

Berlin around the Central Station, with the Federal Chancellery, the Spreebogen, the House of World Cultures, the Reichstag building on the southern edge and the Spree running through the middle. The 1.8 × 1.4 km section holds 2,538 blocks from OpenStreetMap, the tallest buildings measure 84 m, and 19% of the area is green. The Spree takes up 6.5% of the section, with waves, foam along the shore and bridges. People, cars and buses move through it, each with its own destination, plus U-Bahn, S-Bahn and long-distance trains, and trams.

Controls for residents, jobs and new building, for buses, service intervals, traffic lights and a car-free centre act at once: pavements and streets fill up, trains get crowded, houses grow. The city fades out, revealing the tunnels of the U-Bahn, S-Bahn and long-distance rail, water, power and data beneath. Situations such as a rail outage, congestion, a street festival or empty shops show where it gets tight first.

Real are location, streets, buildings, tracks, stops, traffic lights and venues from OpenStreetMap. Traffic, service intervals, residents and jobs per building, and the cable and pipe routes are model assumptions: the model shows connections, not a forecast. The page is for urban and transport planning, politics and public participation, schools, universities and exhibitions.

A city centre that lives

01

A city centre that lives

Berlin around Central Station – main station · Chancellery · Spree: 2,538 building blocks on 2.5 km², streets, tracks and water from OpenStreetMap (as of 30 October 2026). Cars, buses, trains and people are on the move, each with a destination of their own.

As evening falls

02

As evening falls

Dusk in Berlin around Central Station: the windows light up, street lights and headlights trace the streets – seen from a low angle.

What is shown – why – for whom

Qué se muestra Por qué Para quién
Central Station, Chancellery and Spreebogen with 2,538 blocks from OpenStreetMap Por quéShows the district as it lies on the Spree. Para quiénplanning, exhibition
People, cars and buses with their own destinations Por quéShows where it gets full and where it gets tight. Para quiéntransport planning
U-Bahn, S-Bahn and long-distance trains partly in tunnels, trams above ground Por quéShows how much depends on service intervals and space on the trains. Para quiénpublic transport, mobility
Water, power and data beneath the streets Por quéShows the networks you otherwise cannot see. Para quiénutilities, teaching
Shops, restaurants, culture and festivals from OpenStreetMap Por quéShows what makes a district lively. Para quiéncity marketing, economic development
Controls with a city index for mobility, quality of living and city life Por quéShows connections, not a forecast. Para quiénpolitics, participation
What lies beneath the city

03

What lies beneath the city

All networks at once – water blue, power yellow, data turquoise, plus the trains in their tunnels and the flows of people as bands of light.

Riding along

04

Riding along

Trams: line “Invalidenpark – Clara-Jaschke-Straße” – the camera rides along, at every stop people get off and on.

Films from the model

  • Above Berlin around Central Station

    A flight over the city centre with Central Station, Federal Chancellery and Reichstag building – buildings made of blocks, streets, trains and people on the move.

  • From day into night

    Berlin around Central Station by day, at dusk, at night and with street festivals at night – in one slow camera move: windows light up, beams of light over the squares.

  • What lies beneath Berlin around Central Station

    The city fades: below the tunnels of the U-Bahn underground as well as S-Bahn and mainline trains, then water, power and data – the points come from OpenStreetMap, the line routes are assumed.

  • Riding along

    The camera rides along: first trams, then S-Bahn and mainline trains, then a bus – at every stop people get off and on.

  • One slider – the city responds

    The city builds itself from the map data, then the buildings grow by two storeys; the analysis shows residents per hectare and how switching modes and a car-free centre relieve the streets.

  • Using the software

    With the full interface: controls and city index, place card, departure board at the station, following a train, analysis and layers with utilities.

City, networks and transport in the model

  • Section

    main station · Chancellery · Spree – 1,800 × 1,400 m, 2.5 km², OpenStreetMap as of 30 October 2026.

  • Landmarks

    Central Station, Federal Chancellery, Reichstag building and House of World Cultures.

  • Buildings

    2,538 building blocks, buildings up to 84 m, 23 % of the area built up, 19 % green; 43 named buildings and 207 places.

  • Streets

    3,456 path segments and 3,234 nodes with traffic lights, zebra crossings and crossings; pavements along every street.

  • Venues

    202 shops, restaurants, bars and clubs, cultural venues, leisure and independent scene from OpenStreetMap – each one doing well, tight, struggling or closed.

  • Water

    Spree: 6.5 % of the section, with waves, foam along the banks and bridges.

  • Water

    251 hydrants and 167 further points from OpenStreetMap; pipes assumed under the streets.

  • Power

    1,197 street lights, 6 substations, 4 transformer stations and 43 further points from OpenStreetMap; cables drawn schematically.

  • Data

    82 street cabinets and 26 antennas from OpenStreetMap; the network in between is assumed.

  • Underground / Suburban rail

    Tunnels of the U-Bahn underground as well as S-Bahn and mainline trains in true depth below the city.

  • Flows

    Flows of people as arrowed bands of light, visible in every view.

  • U-Bahn underground

    1 line through the section, 2 stations, mostly in tunnels; trains run to a timetable (model), people board and alight at every stop.

  • S-Bahn and mainline trains

    4 lines through the section, 3 stations, partly in tunnels; trains run to a timetable (model), people board and alight at every stop.

  • trams

    2 lines through the section, 5 stations, above ground; trains run to a timetable (model), people board and alight at every stop.

  • Bus

    In the model: ring line from the station with a limited number of seats; 44 bus stops from OpenStreetMap; a full bus glows pink.

  • Cars, walking, cycling

    Cars keep their distance and obey traffic lights, priority and crossing pedestrians; queues take up space. Nobody disappears.

One slider, the whole city

05

One slider, the whole city

Twice as many residents – density analysis: residents per hectare, calm below 150, yellow from 300, pink above 450.

Fire in the district

06

Fire in the district

House fire – flames and smoke over the district; in the model a house catches fire now and then, in the middle of daily life.

What the model can be used for

  • Urban and transport planning

    The switch to bus and rail, denser service or a car-free centre can be adjusted. The analysis colours streets and paths and shows where a decision takes effect elsewhere.

    Para quiénurban planning, transport planning, mobility

  • Changing trains at the Central Station

    Around the Central Station run U-Bahn, S-Bahn and long-distance rail, trams and buses. You see how people change, where service intervals and space on the trains fall short, and what a rail outage sets off.

    Para quiénpublic transport, transport planning, mobility

  • Networks and utilities

    Beneath the city lie tunnels, water, power and data. The points come from OpenStreetMap, the routes are assumed. You see how many networks a city carries.

    Para quiénutilities, infrastructure, teaching

  • School, university, exhibition

    How do living, working, transport and city life connect? The city runs around the clock, from day to night, and the demonstration also runs without anyone at the controls.

    Para quiénschools, universities, museums and exhibitions

Festival at night

07

Festival at night

Street festival at night – stages, beams of light and crowds on the big squares of Berlin around Central Station.

The whole software

08

The whole software

The whole software – city index at the top, city controls on the left, time of day, sound and camera on the right, views and city pulse below.

What you can change

Controls

  • Residents (50–250 %): How many people live here. More people: more trips, fuller pavements and roads, less living space per head.
  • Jobs (50–250 %): How many people work here. More jobs: more commuters by car and train, the centre fills up.
  • New building (up to 2 storeys): Residential and mixed buildings gain storeys: more living space – the buildings visibly grow.
  • Switch to bus & rail (0–80 %): Share of car trips that take the bus and train instead. Frees the roads – needs room on the trains.
  • Traffic lights (priority cars ↔ pedestrians): Long cycles for cars or short ones, with all-way walk, for pedestrians.
  • Car-free centre (radius 0–900 m): Radius around the centre: cars park outside, buses run, pedestrians cross freely.
  • Buses (0–300 %): How many buses run – room for people who switch.
  • Underground frequency (off to triple, normally every 6 min): How often underground, light rail and trams run. More often: shorter waits, more passengers, fewer cars. Here: U-Bahn underground and trams.
  • Suburban rail frequency (off to triple, normally every 10 min): How often suburban and regional trains run. Off: nobody arrives by train, more cars. Here: S-Bahn and mainline trains.
  • Shops (0–200 %): How many shops are open. Fewer: empty units, worse supply, more people drive out by car.
  • Food & drink (0–200 %): Restaurants and cafés. Need guests – residents, workers, visitors; with noise nobody sits outside.
  • Bars & clubs (0–200 %): Nightlife: makes the city worth experiencing – but loud for the neighbours at night.
  • Culture (0–200 %): Museums, theatres, cinemas, concerts. Attract visitors.
  • Independent scene (0–200 %): Cultural centres, studios, community arts – small but important for the experience.
  • Street festivals (0–3): Festivals and events on the big squares: stage, lights, crowds.

Situations

  • Fire: Now and then a house in view catches fire: the flames grow, burn for about a minute and smoke drifts over the district (model).
  • Gridlock: More jobs and residents, traffic lights favouring pedestrians: cars queue, the analysis turns the streets pink.
  • Rail shutdown: Both frequency controls off: the U-Bahn underground, S-Bahn and mainline trains as well as trams stop, nobody arrives by train, more cars push into the city.
  • Street festival: Festivals and events on the big squares: stage, lights, crowds. Experience rises, nights get louder.
  • Clubs closed: Bars and clubs set to zero: the venues turn grey, experience drops, nights get quieter for the neighbours.
  • Empty shops: Fewer residents and only a third of the shops open: shops and restaurants struggle (lens venues: pink struggling, grey closed), more people drive out by car.
  • Roadworks: The scenario generator closes a much-used path for over half an hour when there is a detour.
  • Dusk and night: Time of day (key N): windows, street lights and headlights come on; the clock runs from 18:30 or 22:30.

What the model brings

  • 01

    The real district as a stage

    Streets, houses, tracks and the Spree come from OpenStreetMap. You show Berlin with the Central Station, Chancellery and Reichstag building as it lies, not as a diagram.

  • 02

    See the effect at once

    Every control acts immediately: pavements, streets and trains fill up or empty, and the analysis shows where.

  • 03

    Situations without damage

    Rail outage, congestion, a street festival or empty shops can be triggered. You see where it gets tight first, and set it back.

  • 04

    For big screens and the browser

    Runs in the browser and on large projections, from day to night, with a demonstration that starts without anyone at the controls.

  • Berlin rund um den Hauptbahnhof – Hbf · Kanzleramt · Spree: 2.538 Bausteine auf 2,5 km², Straßen, Gleise und Wasser aus OpenStreetMap (Stand 30.10.2026). Autos, Busse, Bahnen und Menschen sind unterwegs, jeder mit eigenem Ziel.
    Berlin around Central Station – main station · Chancellery · Spree: 2,538 building blocks on 2.5 km², streets, tracks and water from OpenStreetMap (as of 30 October 2026). Cars, buses, trains and people are on the move, each with a destination of their own.
  • Berlin rund um den Hauptbahnhof von der anderen Seite – mit Bundeskanzleramt und Reichstagsgebäude. Häuser bis 84 m hoch.
    Berlin around Central Station from the other side – with Federal Chancellery and Reichstag building. Buildings up to 84 m tall.
  • Quer zum Licht – die Sonne steht im Südwesten; die Gebäudehöhen stammen aus OpenStreetMap oder sind nach Gebäudeart geschätzt, die Grundrisse in Quader zerlegt.
    Across the light – the sun stands in the south-west; building heights come from OpenStreetMap or are estimated by building type, the footprints split into blocks.
  • Bundeskanzleramt – Halbtotale; ringsum 43 benannte Gebäude und 207 Orte aus OpenStreetMap.
    Federal Chancellery – medium shot; around it 43 named buildings and 207 places from OpenStreetMap.
  • Reichstagsgebäude im Stadtgefüge – Straßen als Quader, Gehwege an allen Straßen, 3.456 Wegstücke im Netz.
    Reichstag building in the urban fabric – streets as blocks, pavements along every street, 3,456 path segments in the network.
  • Abend in Berlin rund um den Hauptbahnhof: die Fenster gehen an, Laternen und Scheinwerfer zeichnen die Straßen – aus flachem Winkel.
    Dusk in Berlin around Central Station: the windows light up, street lights and headlights trace the streets – seen from a low angle.
  • Bundeskanzleramt am Abend – Fenster, Laternen und der Verkehr mit Licht.
    Federal Chancellery at dusk – windows, street lights and traffic with headlights on.
  • Nacht in Berlin rund um den Hauptbahnhof: nur noch Fenster, Laternen und Scheinwerfer – die Stadt läuft rund um die Uhr weiter.
    Night in Berlin around Central Station: only windows, street lights and headlights – the city keeps running around the clock.
  • Spree – Wellen, Schaum am Ufer und Brücken; die Wasserflächen (6,5 % des Ausschnitts) stammen aus OpenStreetMap.
    Spree – waves, foam along the banks and bridges; the water areas (6.5 % of the map) come from OpenStreetMap.
  • Schräg von oben – das Straßennetz mit 3.234 Knoten, dazu Ampeln, Zebrastreifen und Querungen aus OpenStreetMap.
    From above at an angle – the street network with 3,234 nodes, plus traffic lights, zebra crossings and crossings from OpenStreetMap.
  • Ebenen: die Stadt wird zum Schleier, darunter liegen die Tunnel von U-Bahn sowie S-Bahn und Fernbahn – 9 Stationen im Ausschnitt.
    Layers: the city becomes a veil, below lie the tunnels of the U-Bahn underground as well as S-Bahn and mainline trains – 9 stations on the map.
  • Wasser unter Berlin rund um den Hauptbahnhof: 251 Hydranten und 167 weitere Punkte aus OpenStreetMap; die Leitungen sind angenommen, unter den Straßen.
    Water beneath Berlin around Central Station: 251 hydrants and 167 further points from OpenStreetMap; the pipes are assumed, under the streets.
  • Strom: 1.197 Straßenleuchten, 6 Umspannstationen, 4 Trafostationen und 43 Erzeuger aus OpenStreetMap – die Leitungen schematisch unter den Straßen.
    Power: 1,197 street lights, 6 substations, 4 transformer stations and 43 generators from OpenStreetMap – the cables drawn schematically under the streets.
  • Daten: 82 Schaltschränke und 26 Antennen aus OpenStreetMap; das Netz dazwischen ist angenommen.
    Data: 82 street cabinets and 26 antennas from OpenStreetMap; the network in between is assumed.
  • Alle Netze zugleich – Wasser blau, Strom gelb, Daten türkis, dazu die Bahnen im Tunnel und die Ströme der Menschen als Lichtbänder.
    All networks at once – water blue, power yellow, data turquoise, plus the trains in their tunnels and the flows of people as bands of light.
  • Ebenen mit Namen – über den Gleisen stehen die Stationen von U-Bahn, S-Bahn und Fernbahn sowie Straßenbahn; in den Ebenen sind sie immer zu sehen.
    Layers with names – the stations of the U-Bahn underground, S-Bahn and mainline trains as well as trams stand above the tracks; in the layers they are always visible.
  • Straßenbahn: Linie „Invalidenpark – Clara-Jaschke-Straße“ – die Kamera fährt mit, an jedem Halt steigen Menschen aus und ein.
    Trams: line “Invalidenpark – Clara-Jaschke-Straße” – the camera rides along, at every stop people get off and on.
  • S-Bahn und Fernbahn: Linie „Invalidenpark – Clara-Jaschke-Straße“ – die Kamera fährt mit, an jedem Halt steigen Menschen aus und ein.
    S-Bahn and mainline trains: line “Invalidenpark – Clara-Jaschke-Straße” – the camera rides along, at every stop people get off and on.
  • Bus – die Kamera fährt mit; an jeder Haltestelle steigen Menschen ein und aus, ist er voll, leuchtet er pink.
    Bus – the camera rides along; at every stop people get on and off, and when it is full it glows pink.
  • Am Hauptbahnhof: ein Zug kommt an, Hunderte steigen aus – gelb suchen sie ihren Weg in die Stadt.
    At the main station: a train arrives and hundreds get off – in yellow they find their way into the city.
  • Analyse Verkehr in Berlin rund um den Hauptbahnhof – grün frei, gelb voll, pink Stau; Säulen zeigen die Wartenden an den Kreuzungen.
    Traffic analysis in Berlin around Central Station – green free, yellow full, pink jammed; columns show the people waiting at junctions.
  • Analyse Gedränge – Menschen auf den Gehwegen, Ringe für Wartende an Ampeln und Bahnsteigen; pink heißt: der Zug war voll.
    Crowding analysis – people on the pavements, rings for those waiting at lights and platforms; pink means the train was full.
  • Stationen beschriftet – 9 Halte von U-Bahn, S-Bahn und Fernbahn sowie Straßenbahn im Ausschnitt, dazu Ankunft und Wege am Bahnhof.
    Stations labelled – 9 stops of the U-Bahn underground, S-Bahn and mainline trains as well as trams on the map, plus arrivals and walks at the station.
  • Neubau – die Wohn- und Mischhäuser werden um zwei Geschosse aufgestockt, Berlin rund um den Hauptbahnhof wächst sichtbar.
    New building – residential and mixed buildings gain two storeys, Berlin around Central Station visibly grows.
  • Doppelt so viele Einwohner – Analyse Dichte: Einwohner je Hektar, ruhig unter 150, gelb ab 300, pink über 450.
    Twice as many residents – density analysis: residents per hectare, calm below 150, yellow from 300, pink above 450.
  • Doppelt so viele Arbeitsplätze – Analyse Arbeit: gelb ab 500, pink über 900 je Hektar; dorthin pendelt die Stadt.
    Twice as many jobs – jobs analysis: yellow from 500, pink above 900 per hectare; that is where the city commutes to.
  • Wohnwert je Viertel – pink schlecht, gelb mittel, grün gut; dahinter Versorgung, Gastronomie, Kultur, Nachtleben, Freizeit, Grün, Ruhe und Platz.
    Liveability per neighbourhood – pink poor, yellow medium, green good; behind it supply, food and drink, culture, nightlife, leisure, green, quiet and space.
  • Angebote der Stadt – 202 Läden, Lokale, Clubs, Kulturorte und Treffpunkte aus OpenStreetMap; grün läuft gut, gelb knapp, pink leidet, grau zu.
    Venues of the city – 202 shops, restaurants, clubs, cultural venues and meeting places from OpenStreetMap; green doing well, yellow tight, pink struggling, grey closed.
  • Autofreie Mitte mit 600 m Radius und 60 % Umstieg auf Bus und Bahn – die Straßen werden grün, die Bahnen voller.
    A car-free centre with a 600 m radius and 60 % switching to bus and rail – the streets turn green, the trains get fuller.
  • Brennpunkte mit Namen und Zahl – wo es am dichtesten und am vollsten ist, steht direkt über der Stadt.
    Hot spots with names and figures – where it is densest and busiest is shown right above the city.
  • Stadt-Regler und Stadt-Index – neun Hebel für Stadt und Verkehr, oben der Index aus Mobilität, Wohnwert und Erlebnis, gemessen am normalen Tag.
    City controls and city index – nine levers for the city and its traffic, at the top the index of mobility, liveability and experience, measured against a normal day.
  • Hausbrand – Feuer und Rauch über dem Viertel; im Modell brennt ab und zu ein Haus, mitten im laufenden Betrieb.
    House fire – flames and smoke over the district; in the model a house catches fire now and then, in the middle of daily life.
  • Brand mit Schild – die Stadt zeigt, wo es brennt: Rauch über dem Viertel.
    Fire with its sign – the city shows where it is burning: smoke over the district.
  • Stau – zweieinhalbmal so viele Arbeitsplätze, mehr Einwohner und Ampeln mit Vorrang für Fußgänger: die Straßen laufen pink voll.
    Gridlock – two and a half times the jobs, more residents and traffic lights favouring pedestrians: the streets fill up in pink.
  • Bahn fällt aus – U-Bahn, S-Bahn und Fernbahn sowie Straßenbahn stehen still, niemand kommt mehr mit dem Zug, mehr Autos drängen in die Stadt.
    Rail shutdown – the U-Bahn underground, S-Bahn and mainline trains as well as trams stand still, nobody arrives by train any more, more cars push into the city.
  • Stadtfest bei Nacht – Bühnen, Lichtkegel und viele Menschen auf den großen Plätzen von Berlin rund um den Hauptbahnhof.
    Street festival at night – stages, beams of light and crowds on the big squares of Berlin around Central Station.
  • Clubs und Bars zu, nur ein Viertel der Lokale offen – die Angebote färben sich grau, das Erlebnis sinkt, nachts wird es leiser.
    Clubs and bars closed, only a quarter of restaurants open – the venues turn grey, the experience drops, nights get quieter.
  • Leerstand – halb so viele Einwohner, nur 30 % der Läden offen: Läden und Lokale leiden, die Stadt wird leer.
    Empty shops – half the residents, only 30 % of shops open: shops and restaurants struggle, the city empties.
  • Die ganze Software – Stadt-Index oben, Stadt-Regler links, Tageszeit, Ton und Kamera rechts, Ansichten und Stadtpuls unten.
    The whole software – city index at the top, city controls on the left, time of day, sound and camera on the right, views and city pulse below.
  • Klick in die Stadt – die Ortskarte nennt den Ort und zeigt Menschen, Autos und Lärm mit kleiner Verlaufslinie.
    Click into the city – the place card names the spot and shows people, cars and noise with a small trend line.
  • Am Bahnhof – die Abfahrtstafel zeigt Linie, Ziel und Minuten, dazu die Wartenden und den nächsten Zug.
    At the station – the departure board shows line, destination and minutes, plus the people waiting and the next train.
  • Zug angetippt – die Kamera fährt mit, die Karte nennt Linie, Ziel, nächsten Halt, Tempo und Fahrgäste.
    Train tapped – the camera rides along, the card names line, destination, next stop, speed and passengers.
  • Stadtpuls – Stau, Wartezeit, Lärm, CO₂, Pünktlichkeit und Wege am Ziel, jeweils gegen den normalen Tag gerechnet.
    City pulse – congestion, waiting time, noise, CO₂, punctuality and completed trips, each compared with a normal day.
  • Analyse mit Legende – Linsen für Dichte, Arbeit, Verkehr, Gedränge, Wohnwert und Angebote, rechts der Stadtpuls.
    Analysis with legend – lenses for density, jobs, traffic, crowding, liveability and venues, the city pulse on the right.
  • Ebenen mit Leiste und Versorgungstafel – Leitungslänge, Punkte aus OpenStreetMap, Abstand der Gebäude und Abdeckung je Netz.
    Layers with toolbar and utilities panel – line length, points from OpenStreetMap, distance of buildings and coverage per network.
  • Leben und Erlebnis – Läden, Gastronomie, Clubs, Kultur, freie Szene und Stadtfeste als eigene Regler, rechts ihre Wirkung.
    Life and experience – shops, food and drink, clubs, culture, the independent scene and street festivals as controls of their own, their effect on the right.
  • Stadtwahl – 15 Stadtkerne von Bochum bis New York, jeder aus OpenStreetMap; hier ist Berlin rund um den Hauptbahnhof gewählt.
    Choosing a city – 15 city centres from Bochum to New York, each from OpenStreetMap; here Berlin around Central Station is selected.
  • Pause mit Bedienung – Maus, Tastatur und Touch: ziehen, drehen, zoomen, Ansicht wechseln, Tageszeit mit N.
    Pause with controls – mouse, keyboard and touch: drag, rotate, zoom, change view, time of day with N.

Your city as a model

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Minimal City: Berlin · Hauptbahnhof, Kanzleramt und Spree

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Basis and limits

Real are the location, the street and path network, building footprints and heights (where mapped, otherwise estimated by building type), tracks, stops, traffic lights, venues and utility points of Berlin around Central Station – from OpenStreetMap, as of 30 October 2026. Traffic, demand, timetables, signal plans, residents and jobs as well as the utility line routes are model assumptions: the game shows relationships, not a traffic forecast.

Public sources the model is based on:

  • OpenStreetMap contributors, ODbL 1.0 – data as of 30 October 2026
  • Overpass API (one-off retrieval of the OSM data)
  • Model assumptions: demand, timetables, signal plans, capacities, residents and jobs per building, utility line routes

More cities in the model

← Minimal City

Real are location, streets, buildings, tracks, stops and venues (OpenStreetMap). Traffic, service intervals, residents, jobs and network routes are model assumptions. With your data, the model shows your city and your questions.