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Simulation · Minimal City · Ruhr area

Dortmund · city centre with Westenhellweg

Dortmund's city centre inside the Wallring 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.

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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.

Dortmund's city centre inside the Wallring, from the main station along the Westenhellweg to the Reinoldi and Petri churches, with the football museum, the concert hall, the opera house and the Dortmunder U. The 1.9 × 1.6 km section holds 7,575 blocks from OpenStreetMap, with buildings up to 92 m. People, cars and buses move through it, each with its own destination, plus light rail and trams, S-Bahn and regional trains.

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 rail tunnels, 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

Dortmund – main station · Westenhellweg · Football Museum: 7,575 building blocks on 3.1 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 Dortmund: the windows light up, street lights and headlights trace the streets – seen from a low angle.

What is shown – why – for whom

What is shown Why For whom
Centre inside the Wallring with 7,575 blocks from OpenStreetMap WhyShows the city as it lies, from the main station to the Dortmunder U. For whomplanning, exhibition
People, cars and buses with their own destinations WhyShows where it gets full and where it gets tight. For whomtransport planning
Light rail and trams, S-Bahn and regional trains, partly in tunnels WhyShows how much depends on service intervals and space on the trains. For whompublic transport, mobility
Water, power and data beneath the streets WhyShows the networks you otherwise cannot see. For whomutilities, teaching
Shops, restaurants, culture and festivals from OpenStreetMap WhyShows what makes a city centre lively. For whomcity marketing, economic development
Controls with a city index for mobility, quality of living and city life WhyShows connections, not a forecast. For whompolitics, 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

Light rail and trams: line “Dortmund Möllerbrücke – Brügmannplatz” – the camera rides along, at every stop people get off and on.

Films from the model

  • Above Dortmund

    A flight over the city centre with St Peter’s church, St Reinold’s church and Dortmunder U – buildings made of blocks, streets, trains and people on the move.

  • From day into night

    Dortmund 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 Dortmund

    The city fades: below the tunnels of the light rail and trams as well as suburban and regional trains, then water, power and data – the points come from OpenStreetMap, the line routes are assumed.

  • Riding along

    The camera rides along: first light rail and trams, then suburban and regional 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 · Westenhellweg · Football Museum – 1,900 × 1,640 m, 3.1 km², OpenStreetMap as of 30 October 2026.

  • Landmarks

    St Peter’s church, St Reinold’s church, Dortmunder U and Football Museum.

  • Buildings

    7,575 building blocks, buildings up to 92 m, 31 % of the area built up, 10 % green; 41 named buildings and 351 places.

  • Streets

    5,495 path segments and 4,951 nodes with traffic lights, zebra crossings and crossings; pavements along every street.

  • Venues

    1,019 shops, restaurants, bars and clubs, cultural venues, leisure and independent scene from OpenStreetMap – each one doing well, tight, struggling or closed.

  • Water

    153 hydrants and 43 further points from OpenStreetMap; pipes assumed under the streets.

  • Power

    725 street lights, 5 substations, 1 transformer station and 14 further points from OpenStreetMap; cables drawn schematically.

  • Data

    48 street cabinets, 2 exchanges and 42 antennas from OpenStreetMap; the network in between is assumed.

  • Underground / Suburban rail

    Tunnels of the light rail and trams as well as suburban and regional trains in true depth below the city.

  • Flows

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

  • light rail and trams

    3 lines through the section, 11 stations, mostly in tunnels; trains run to a timetable (model), people board and alight at every stop.

  • suburban and regional trains

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

  • Bus

    In the model: Fanshuttle with a limited number of seats; 64 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, for example around the Wallring.

    For whomurban planning, transport planning, mobility

  • From the main station into the centre

    How do people spread from the main station along the Westenhellweg into the centre? With service intervals, traffic lights and a car-free radius you can try out where the routes get dense.

    For whomtransport planning, city marketing, retail

  • Networks and utilities

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

    For whomutilities, 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.

    For whomschools, 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 Dortmund.

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: light rail 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: suburban and regional 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 light rail and trams as well as suburban and regional trains 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.
  • 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 centre as a stage

    Streets, houses and tracks come from OpenStreetMap. You show Dortmund with the Westenhellweg, the churches and the football museum 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.

  • Dortmund – main station · Westenhellweg · Football Museum: 7,575 building blocks on 3.1 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.
    Dortmund – main station · Westenhellweg · Football Museum: 7,575 building blocks on 3.1 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.
  • Dortmund from the other side – with St Reinold’s church and Dortmunder U. Buildings up to 92 m tall.
    Dortmund from the other side – with St Reinold’s church and Dortmunder U. Buildings up to 92 m tall.
  • 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.
    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.
  • St Reinold’s church – medium shot; around it 41 named buildings and 351 places from OpenStreetMap.
    St Reinold’s church – medium shot; around it 41 named buildings and 351 places from OpenStreetMap.
  • Dortmunder U in the urban fabric – streets as blocks, pavements along every street, 5,495 path segments in the network.
    Dortmunder U in the urban fabric – streets as blocks, pavements along every street, 5,495 path segments in the network.
  • Dusk in Dortmund: the windows light up, street lights and headlights trace the streets – seen from a low angle.
    Dusk in Dortmund: the windows light up, street lights and headlights trace the streets – seen from a low angle.
  • St Reinold’s church at dusk – windows, street lights and traffic with headlights on.
    St Reinold’s church at dusk – windows, street lights and traffic with headlights on.
  • Night in Dortmund: only windows, street lights and headlights – the city keeps running around the clock.
    Night in Dortmund: only windows, street lights and headlights – the city keeps running around the clock.
  • Dortmund from afar – 1,900 × 1,640 m of city centre, 31 % of the area built up, 10 % green.
    Dortmund from afar – 1,900 × 1,640 m of city centre, 31 % of the area built up, 10 % green.
  • From above at an angle – the street network with 4,951 nodes, plus traffic lights, zebra crossings and crossings from OpenStreetMap.
    From above at an angle – the street network with 4,951 nodes, plus traffic lights, zebra crossings and crossings from OpenStreetMap.
  • Layers: the city becomes a veil, below lie the tunnels of the light rail and trams as well as suburban and regional trains – 13 stations on the map.
    Layers: the city becomes a veil, below lie the tunnels of the light rail and trams as well as suburban and regional trains – 13 stations on the map.
  • Water beneath Dortmund: 153 hydrants and 43 further points from OpenStreetMap; the pipes are assumed, under the streets.
    Water beneath Dortmund: 153 hydrants and 43 further points from OpenStreetMap; the pipes are assumed, under the streets.
  • Power: 725 street lights, 5 substations, 1 transformer station, 2 generators and 12 further points from OpenStreetMap – the cables drawn schematically under the streets.
    Power: 725 street lights, 5 substations, 1 transformer station, 2 generators and 12 further points from OpenStreetMap – the cables drawn schematically under the streets.
  • Data: 48 street cabinets, 2 exchanges and 42 antennas from OpenStreetMap; the network in between is assumed.
    Data: 48 street cabinets, 2 exchanges and 42 antennas from OpenStreetMap; the network in between is assumed.
  • 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.
    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.
  • Light rail and trams: line “Dortmund Möllerbrücke – Brügmannplatz” – the camera rides along, at every stop people get off and on.
    Light rail and trams: line “Dortmund Möllerbrücke – Brügmannplatz” – the camera rides along, at every stop people get off and on.
  • Suburban and regional trains: line “Dortmund Hbf” – the camera rides along, at every stop people get off and on.
    Suburban and regional trains: line “Dortmund Hbf” – the camera rides along, at every stop people get off and on.
  • At the station: a train arrives and hundreds get off – in yellow they find their way into the city.
    At the station: a train arrives and hundreds get off – in yellow they find their way into the city.
  • Traffic analysis in Dortmund – green free, yellow full, pink jammed; columns show the people waiting at junctions.
    Traffic analysis in Dortmund – green free, yellow full, pink jammed; columns show the people waiting at junctions.
  • Crowding analysis – people on the pavements, rings for those waiting at lights and platforms; pink means the train was full.
    Crowding analysis – people on the pavements, rings for those waiting at lights and platforms; pink means the train was full.
  • Stations labelled – 13 stops of the light rail and trams as well as suburban and regional trains on the map, plus arrivals and walks at the station.
    Stations labelled – 13 stops of the light rail and trams as well as suburban and regional trains on the map, plus arrivals and walks at the station.
  • New building – residential and mixed buildings gain two storeys, Dortmund visibly grows.
    New building – residential and mixed buildings gain two storeys, Dortmund visibly grows.
  • Twice as many residents – density analysis: residents per hectare, calm below 150, yellow from 300, pink above 450.
    Twice as many residents – density analysis: residents per hectare, calm below 150, yellow from 300, pink above 450.
  • Twice as many jobs – jobs analysis: yellow from 500, pink above 900 per hectare; that is where the city commutes to.
    Twice as many jobs – jobs analysis: yellow from 500, pink above 900 per hectare; that is where the city commutes to.
  • Liveability per neighbourhood – pink poor, yellow medium, green good; behind it supply, food and drink, culture, nightlife, leisure, green, quiet and space.
    Liveability per neighbourhood – pink poor, yellow medium, green good; behind it supply, food and drink, culture, nightlife, leisure, green, quiet and space.
  • Venues of the city – 1,019 shops, restaurants, clubs, cultural venues and meeting places from OpenStreetMap; green doing well, yellow tight, pink struggling, grey closed.
    Venues of the city – 1,019 shops, restaurants, clubs, cultural venues and meeting places from OpenStreetMap; green doing well, yellow tight, pink struggling, grey closed.
  • A car-free centre with a 600 m radius and 60 % switching to bus and rail – the streets turn green, the trains get fuller.
    A car-free centre with a 600 m radius and 60 % switching to bus and rail – the streets turn green, the trains get fuller.
  • Hot spots with names and figures – where it is densest and busiest is shown right above the city.
    Hot spots with names and figures – where it is densest and busiest is shown right above the city.
  • 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.
    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.
  • House fire – flames and smoke over the district; in the model a house catches fire now and then, in the middle of daily life.
    House fire – flames and smoke over the district; in the model a house catches fire now and then, in the middle of daily life.
  • Fire with its sign – the city shows where it is burning: smoke over the district.
    Fire with its sign – the city shows where it is burning: smoke over the district.
  • Gridlock – two and a half times the jobs, more residents and traffic lights favouring pedestrians: the streets fill up in pink.
    Gridlock – two and a half times the jobs, more residents and traffic lights favouring pedestrians: the streets fill up in pink.
  • Rail shutdown – the light rail and trams as well as suburban and regional trains stand still, nobody arrives by train any more, more cars push into the city.
    Rail shutdown – the light rail and trams as well as suburban and regional trains stand still, nobody arrives by train any more, more cars push into the city.
  • Street festival at night – stages, beams of light and crowds on the big squares of Dortmund.
    Street festival at night – stages, beams of light and crowds on the big squares of Dortmund.
  • Clubs and bars closed, only a quarter of restaurants open – the venues turn grey, the experience drops, nights get quieter.
    Clubs and bars closed, only a quarter of restaurants open – the venues turn grey, the experience drops, nights get quieter.
  • Empty shops – half the residents, only 30 % of shops open: shops and restaurants struggle, the city empties.
    Empty shops – half the residents, only 30 % of shops open: shops and restaurants struggle, the city empties.
  • 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.
    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.
  • Click into the city – the place card names the spot and shows people, cars and noise with a small trend line.
    Click into the city – the place card names the spot and shows people, cars and noise with a small trend line.
  • Train tapped – the camera rides along, the card names line, destination, next stop, speed and passengers.
    Train tapped – the camera rides along, the card names line, destination, next stop, speed and passengers.
  • City pulse – congestion, waiting time, noise, CO₂, punctuality and completed trips, each compared with a normal day.
    City pulse – congestion, waiting time, noise, CO₂, punctuality and completed trips, each compared with a normal day.
  • Analysis with legend – lenses for density, jobs, traffic, crowding, liveability and venues, the city pulse on the right.
    Analysis with legend – lenses for density, jobs, traffic, crowding, liveability and venues, the city pulse on the right.
  • Layers with toolbar and utilities panel – line length, points from OpenStreetMap, distance of buildings and coverage per network.
    Layers with toolbar and utilities panel – line length, points from OpenStreetMap, distance of buildings and coverage per network.
  • 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.
    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.
  • Choosing a city – 15 city centres from Bochum to New York, each from OpenStreetMap; here Dortmund is selected.
    Choosing a city – 15 city centres from Bochum to New York, each from OpenStreetMap; here Dortmund is selected.
  • Pause with controls – mouse, keyboard and touch: drag, rotate, zoom, change view, time of day with 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: Dortmund · Innenstadt mit Westenhellweg

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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 Dortmund – 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.