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Digital twin

A digital twin
of your region.

The Replan digital twin models the street network, timetable and population of a region: every simulated person plans a day and reacts again when lines, fares, zones or streets change.

A digital twin for transport planning is a model of the region on which measures are tested before they are built. Replan builds it from open data in one working day and calibrates it with your counts. Replan Transit plans the service on it, Replan SIM simulates the demand.

Data sources

Built from open data, refined with yours.

Street network

OpenStreetMap for roads, paths and footways.

Timetable

GTFS for lines and departures, added to with your planning versions.

Population

Census for residents and jobs, a synthetic population with age, household, income and car access.

Travel behaviour

MiD, SrV and Mikrozensus for trips, modes and daily schedules.

Your data

Counts, ticketing data and your current network calibrate the twin. No personal data is needed.

Existing models

Existing traffic models are converted where suitable.

Build

From the first day to a calibrated twin.

01

Week 1

A first digital twin of the region runs, built from open data.

02

Weeks 2 to 4

Timetables, planning versions, vehicle types and cost parameters from your current system.

03

Weeks 4 to 8

Calibration against your counts, checks on cases your team knows. Every deviation is visible.

04

Go-live

Four training sessions, a short guide, and the same team stays. Onboarding

Results

What the twin shows.

Demand

Boardings and alightings per stop, loads per section, transfers.

Mode choice

Modal split shift per scenario, baseline against variant.

Effects on groups

Who gains and who pays, by income, age and district.

Service and cost

Lines, timetable, blocks and cost in Replan Transit on the same twin. Transit service planning

Comparison

Classic traffic model and digital twin.

Macroscopic traffic modelWith Replan
Basic unitZones and matricesPeople with a daily plan
ResultLoads per link and lineLoads and effects per person, group and time of day
Service planningUsually a separate toolReplan Transit on the same twin
DataSurveys and countsOpen data, refined with counts and ticketing data
AccessDepends on the toolIn the browser, results as link, map, table and GIS layer

Typical tool types, not single products. Many teams use both side by side.

In use

Where Replan twins run.

Studies with Replan SIM

MOIA (Hamburg), Klimaschutzrat Berlin, Netivei Ayalon (Israel), IZES (Saarbrücken) and HSU (Hamburg).

Planning with Replan Transit

HAVAG (Halle), LVB (Leipzig), MDV (Mitteldeutschland), THÜSAC (Altenburger Land), NASA GmbH (Sachsen-Anhalt) and MUKMAV (Saarland).

Questions and answers

Frequently asked questions.

What is a digital twin in transport?

A digital twin in transport is a model of a city or region with street network, timetable and population, on which measures are tested before they are built. In Replan every simulated person plans a day and reacts to changes in service, fares or streets.

How fast is a digital twin ready?

A first digital twin of any German region is built from open data in one working day. Calibration against your counts and checks on known cases follow within a few weeks. Onboarding and training →

What data does the twin need?

To start, only open data: OpenStreetMap, GTFS, census, MiD, SrV and Mikrozensus. Your counts, ticketing data and planning versions refine it. No personal data is needed.

What is the simulation built on?

On MATSim, an open simulation framework from TU Berlin and ETH Zürich. The twin is calibrated against passenger counts, and the method is peer-reviewed in Transportation Research Record 2025. MATSim explained in one minute →

Who owns the twin and where is the data?

The twin built for you is yours. It sits in its own tenant, encrypted and hosted in Europe, and can be exported in open formats at any time.

Get started

Bring your region.

In 30 minutes we show a digital twin of your region and run one question: a line, a fare or a zone.

sales@replan.city