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Nairobi · Mobility & logistics

Transport.
Explore journeys, fares and commute records.

Inspect passenger journeys, fares and boarding context, or follow a complete resident commute in the interactive explorer.

Public sample available

Published domain facts

Live Transport Routes
200
Historical range
1940–2026
Certification checks
22
Live Trip Records
98,033,028

Overview

Domain scope

Inspect passenger journeys, fares and boarding context, or follow a complete resident commute in the interactive explorer.

Read the published guide →

Known limits

Early decades are reconstructed; ownership evidence is contextual, without a precise city stock split. The refreshed Nairobi release reports passing realism checks, with fleet scale near the reference band’s lower edge. Visible samples are semantic illustrations, not captured live queries.

Review the source limits →
Full scope reference 2 documented sections
Published domain scope.

Published domain scope.

Follow synthetic journeys, modes and destinations through time. Transport records describe travel; vehicle ownership and government fleet operations remain separate domains.

  • Trace a resident's outward and return journey
  • Compare commute dates, fares and vehicles
  • Inspect the evidence behind transit replays
Live Transport Routes
200
Historical range
1940–2026
Certification checks
22
Live Trip Records
98,033,028
Domain scope.

Domain scope.

Inspect the published scope and deployment boundaries.

Read the published detail

FCTE’s Transport domain represents the city’s commercial mobility ecosystem: transport operators, PSV/matatu vehicles, drivers and crews, routes, stops, licenses, fares and individual journeys. Trips form the operational layer, allowing fleet utilization, passenger movement, route activity, travel demand, operating economics and network performance to be studied through time rather than as isolated snapshots.

It does not represent every registered vehicle in the city. Personal and institutional ownership belongs in Vehicles → , while government-owned operational assets belong in Fleet → . Transport instead answers the movement question: how vehicles become services, services become journeys, and journeys connect people to the city.

Because Transport is connected to the wider City Twin™, movement can be analyzed alongside population , employment , businesses , housing , infrastructure and geography — making it possible to study how urban growth and changing demand reshape mobility across Nairobi.

Samples & fields

Published sample records.

Free passenger journey sample · rows and field definitions

Free passenger journey sample

Resident nameJourney dateRoute nameBoarding stageAlighting stageVehicle typePassenger fare (local currency)Journey endpoint context
Kiura Owuor2026-01-06Route 393 - Karen Hub ShuttleLangata/Karen StageKencom Bus StopShuttle65.00HOME_TO_WORK_WARD
Khisa Mulama2025-01-08Route 203 - Kangemi to DonholmDonholm StageKangemi StageShuttle65.00HOME_TO_WORK_WARD
Mutiso Tuwei2022-02-20Route 215 - Kawangware to KasaraniKawangware StageKasarani StageShuttle65.00HOME_TO_WORK_WARD

Showing 3 of 100 sample rows and 8 of 67 fields. “Not recorded” is a display label; downloads retain original values.

Published field definitions · 8 visible fields

Resident name

Supplied name of the synthetic resident; not a real passenger identity.

Original field: SyntheticResident
Example: Kiura Owuor

Journey date

Date assigned to this journey by the source.

Original field: JourneyDate
Example: 2026-01-06

Route name

Supplied route name. A named service is not a physical road-segment identifier.

Original field: RouteName
Example: Route 393 - Karen Hub Shuttle

Boarding stage

Name supplied for the passenger’s boarding stage.

Original field: BoardingStage
Example: Langata/Karen Stage

Alighting stage

Name supplied for the passenger’s alighting stage.

Original field: AlightingStage
Example: Kencom Bus Stop

Vehicle type

Vehicle class supplied for the trip.

Original field: VehicleType
Example: Shuttle

Passenger fare (local currency)

Fare for this passenger journey in the city’s local currency. It is distinct from whole-trip revenue.

Original field: FareLocal
Example: 65.00

Journey endpoint context

Source classification comparing journey endpoint wards with available home and work wards. It does not establish trip purpose, a return trip or a transfer.

Original field: JourneyEndpointContext
Example: HOME_TO_WORK_WARD

Complete published field dictionary · 67 fields
ResultSetSample collection
Source label identifying this extract.Example: TRANSPORT_RESEARCH_SAMPLE_100
SampleIdSample number
Row number assigned in the supplied sample. Original order is retained.Example: 1
DatasetGrainRecord type
One passenger journey per row. Boarding and alighting belong to the same journey.Example: PassengerJourney
ModelAsOfDateModel reference date
Reference date of the supplied model extract, not the date of every journey.Example: 2026-07-02
JourneyEndpointContextJourney endpoint context
Source classification comparing journey endpoint wards with available home and work wards. It does not establish trip purpose, a return trip or a transfer.Example: HOME_TO_WORK_WARD
JourneyIdJourney reference
Identifier for this passenger journey. All 100 journey identifiers are distinct in this file.Example: 3615
JourneyGroupIdJourney group reference
Journey grouping identifier supplied by the source. A group does not by itself establish a transfer or return trip.Example: 3615
TripIdTrip reference
Identifier for the vehicle trip carrying this passenger. Other passengers may share a trip.Example: 95953078
CitizenIdCitizen reference
Synthetic resident identifier supplied with this journey. Separate free domain samples are not guaranteed to contain the same resident.Example: 4536786
SyntheticResidentResident name
Supplied name of the synthetic resident; not a real passenger identity.Example: Kiura Owuor
GenderGender
Resident gender value exactly as supplied.Example: M
DOBDate of birth
Supplied synthetic resident date of birth.Example: 1998-06-10
AgeAtJourneyAge at journey
Resident age at the journey, as supplied.Example: 27
JourneyDateJourney date
Date assigned to this journey by the source.Example: 2026-01-06
BoardedUtcBoarding time (UTC)
Boarding timestamp in UTC, preserving the original precision. No local-time conversion is applied.Example: 2026-01-06 12:49:00.000
AlightedUtcAlighting time (UTC)
Alighting timestamp in UTC, preserving the original precision. No local-time conversion is applied.Example: 2026-01-06 13:39:00.000
JourneyDurationMinutesJourney duration (minutes)
Elapsed minutes for this passenger journey, as supplied.Example: 50
FareLocalPassenger fare (local currency)
Fare for this passenger journey in the city’s local currency. It is distinct from whole-trip revenue.Example: 65.00
PaymentMethodPayment method
Payment method supplied for this passenger journey.Example: Cash
RouteIdRoute reference
Identifier of the supplied transport route.Example: 175
RouteCodeRoute code
Source route code, preserved as text including leading zeros.Example: 175
RouteNameRoute name
Supplied route name. A named service is not a physical road-segment identifier.Example: Route 393 - Karen Hub Shuttle
RouteTypeRoute type
Route service category supplied by the source.Example: Shuttle
RouteStatusAtSnapshotRoute status at snapshot
Route status at the model snapshot. It may differ from the status on a historical journey date.Example: Active
RouteOriginRoute origin
Reference origin of the named route. It may differ from this passenger’s boarding stage.Example: Karen Hub
RouteDestinationRoute destination
Reference destination of the named route. It may differ from this passenger’s alighting stage.Example: CBD
RouteReferenceDistanceKmRoute reference distance (km)
Reference length of the route in kilometres, not measured passenger distance or GPS travel distance.Example: 18.00
DirectionDirection
Source direction label for the journey within its service.Example: Inbound
RouteOperatorIdRoute operator reference
Operator identifier supplied for the route.Example: 176
VehicleOperatorIdVehicle operator reference
Operator identifier supplied for the vehicle.Example: 176
RouteVehicleOperatorMatchRoute and vehicle operators match
Source flag for whether the route and vehicle operator identifiers agree.Example: 1
BoardingStageIdBoarding stage reference
Identifier of the passenger’s boarding stage.Example: 6
BoardingStageCodeBoarding stage code
Source code of the boarding stage, preserved as text.Example: STG-014
BoardingStageBoarding stage
Name supplied for the passenger’s boarding stage.Example: Langata/Karen Stage
BoardingStageTypeBoarding stage type
Source category of the boarding stage.Example: EXCHANGE
BoardingWardIdBoarding ward reference
Ward identifier supplied for the boarding stage.Example: 16
BoardingWardBoarding ward
Ward name supplied for the boarding stage.Example: Karen
AlightingStageIdAlighting stage reference
Identifier of the passenger’s alighting stage.Example: 1
AlightingStageCodeAlighting stage code
Source code of the alighting stage, preserved as text.Example: STG-002
AlightingStageAlighting stage
Name supplied for the passenger’s alighting stage.Example: Kencom Bus Stop
AlightingStageTypeAlighting stage type
Source category of the alighting stage.Example: EXCHANGE
AlightingWardIdAlighting ward reference
Ward identifier supplied for the alighting stage.Example: 77
AlightingWardAlighting ward
Ward name supplied for the alighting stage.Example: Nairobi Central
CrossWardJourneyCrosses ward boundaries
Source flag indicating different boarding and alighting wards.Example: 1
VehicleIdVehicle reference
Identifier of the public transport vehicle used for the trip.Example: 9637
VehicleTypeVehicle type
Vehicle class supplied for the trip.Example: Shuttle
FuelTypeFuel type
Fuel category supplied for the vehicle.Example: Diesel
SeatCapacitySeat capacity
Supplied seating capacity. This is distinct from the trip’s passenger count.Example: 17
YearOfManufactureYear of manufacture
Supplied vehicle manufacture year. No exact manufacture date is inferred.Example: 2015
VehicleStatusAtSnapshotVehicle status at snapshot
Vehicle status at the model snapshot. A decommissioned vehicle can have earlier journey records.Example: Decommissioned
DriverCitizenIdDriver citizen reference
Synthetic resident identifier supplied for the driver.Example: 246413
PassengerCountPassenger count
Passenger count for the whole vehicle trip, not the number of sample rows for this journey.Example: 6
TripRevenueLocalWhole-trip revenue (local currency)
Revenue supplied for the whole vehicle trip. Do not treat it as this passenger’s fare or sum it across repeated trip references.Example: 390.00
HouseholdIdHousehold reference
Household identifier supplied for the resident’s journey-date context. NULL means no household context is supplied.Example: 1494319
HomeWardIdHome ward reference
Home ward identifier supplied for the resident’s journey-date context.Example: 16
HomeWardAtJourneyHome ward at journey
Home ward name supplied for the journey date, where available.Example: Karen
HasAsOfHouseholdContextHousehold context available
Source flag indicating household context is available for the journey date.Example: 1
ContractIdContract reference
Employment contract identifier supplied for the journey-date context, where available.Example: 46876
EmploymentStartDateEmployment start date
Start date of the supplied employment context. This is not the journey date.Example: 2020-09-09
EmploymentEndDateEmployment end date
End date of the supplied employment context. NULL is preserved without inventing an end date.Example: 2026-07-02
EmployerIdEmployer reference
Employer identifier supplied for the journey-date context, where available.Example: 3652
EmployerNameEmployer name
Synthetic employer name supplied for the journey-date context.Example: HEALTHCARE Employer 0003652
WorkWardIdWork ward reference
Work ward identifier supplied for the journey-date context.Example: 77
WorkWardAtJourneyWork ward at journey
Work ward name supplied for the journey date, where available.Example: Nairobi Central
HasAsOfEmploymentContextEmployment context available
Source flag indicating employment context is available for the journey date.Example: 1
RichnessScoreSource richness score
Source-provided richness score retained unchanged. It is not a marketplace quality rating or a statistical sampling weight.Example: 8
SampleHashSource sample hash
Original source sample hash retained as text. Download integrity is recorded separately with a SHA-256 file checksum.Example: 0x002084817AA0AE50FAB428259AE20458684060DD06450A67C9260852B684162E
Download complete field guide JSON ↓
Additional records and schema context 1 documented sections
Records and relationships.

Records and relationships.

Inspect representative records, fields and relationships.

Read the published detail

Showing representative public entity families. View evidence & lineage →

Representative Nairobi mobility record shape at the public semantic level. Exact physical fields, row volumes and generation methods are controlled.

EntityRepresentsConnected to
VehicleA commercial/PSV vehicle in an operator's fleetOperator, Route, Trip
PrivateVehicleA household or business-owned vehicleCitizen, Household, Business
DriverLicenseA driver's license, category and renewal historyCitizen, LicenseRenewal
RouteA defined path between an origin and destinationOperator, Stage, Trip
StageA named boarding/alighting point (terminus, exchange, roadside)Route, PassengerJourney
TripA single vehicle journey along a routeVehicle, Route, Crew
PassengerJourneyAn individual passenger's boarding-to-alighting recordCitizen, Trip, Stage
RoutePerformanceAggregated delay/occupancy performance per routeRoute, Employment (via a cross-domain consistency check)
OriginDestinationPeriodFare BandPayment Context
KencomNgaraMorning peakLow–midCashless
WestlandsCBDMorning peakMidCashless
KasaraniPanganiMorning peakLow–midCash
GithuraiCBDMorning peakMidCashless

Connections

Known and possible relationships

Review the supported links between domains and their availability.

Domain or contextRelationship and published scope
DemographicsResident and driver identity supplies lifecycle context for mobility records.
Households and EmploymentHome and work context support commute analysis when supplied. They do not establish universal household-to-vehicle or employment-to-trip joins.
GeographyWards and stage locations place routes and journeys in the city.
BusinessOperator-to-business context is documented for commercial transport.
InsuranceAccident claims have a guarded insurance relationship where supported by the city release.
Finance contextFares, fees and fuel spend describe journey economics; they are not asserted as links to bank accounts or government budget records.
Fleet and VehiclesCommercial transport, government fleets and private vehicle ownership are distinct models. Similar vehicle labels are not a cross-domain identity link.
RoadsPlanned relationship only. A named route is not a physical road segment, and the guide reports no road-segment relationship today.
Full relationship reference 1 documented sections
Connected records.

Connected records.

Review the supported links between domains and their availability.

Read the published detail

Connections follow the published domain scope. Optional, contextual and planned relationships retain their stated limits below.

Domain or contextRelationship and published scope
DemographicsResident and driver identity supplies lifecycle context for mobility records.
Households and EmploymentHome and work context support commute analysis when supplied. They do not establish universal household-to-vehicle or employment-to-trip joins.
GeographyWards and stage locations place routes and journeys in the city.
BusinessOperator-to-business context is documented for commercial transport.
InsuranceAccident claims have a guarded insurance relationship where supported by the city release.
Finance contextFares, fees and fuel spend describe journey economics; they are not asserted as links to bank accounts or government budget records.
Fleet and VehiclesCommercial transport, government fleets and private vehicle ownership are distinct models. Similar vehicle labels are not a cross-domain identity link.
RoadsPlanned relationship only. A named route is not a physical road segment, and the guide reports no road-segment relationship today.

Domain guide

Transport · archived guide edition

Publication revision 10 September 2026; evidence dates retained

Counts, prices and “live/today” certification statements reflect this dated edition. They are not a current rerun or offer. The current scope, known limits and accepted quote take priority.

Published scope and limits

Early decades are reconstructed; ownership evidence is contextual, without a precise city stock split. The refreshed Nairobi release reports passing realism checks, with fleet scale near the reference band’s lower edge. Visible samples are semantic illustrations, not captured live queries.

Read the source limits →
Accessible HTML reference 2 documented sections
Modelled entities.

Modelled entities.

Explore the entities and states represented by this domain.

Read the published detail

Individual, business, government, diplomatic, parastatal and NGO ownership — the household side of transport, distinct from commercial fleets. See the dedicated Vehicles → page for ownership, registration and multi-vehicle detail.

Licensing, categories and renewal chronology, age-gated against each citizen's real date of birth.

Routes, stops, operator patterns and service structures for buses, matatus and other formal shared-mobility services across Nairobi.

Ownership models and route types that reflect how Nairobi matatu, bus and other commercial transport operations actually run, not a formalized fiction of them.

Vehicle-level trips and passenger-level journeys, boarding and alighting at named stages.

Crew, maintenance, fares, ticketing, enforcement and accidents — the operational layer behind every trip.

Transport does not claim to reproduce real individuals, vehicles or journeys. Every driver, vehicle, route and trip is synthetic — generated against real regulatory, fleet and demand benchmarks for Nairobi, not sampled from any real transport system.

Histories through time.

Histories through time.

Inspect dated lifecycle transitions and historical boundaries.

Read the published detail

Every vehicle, license and journey is dated against the same citizen and household timeline used by every other domain — not generated independently and hoped to line up.

Insured is labeled Planned because AccidentClaim currently holds a guarded relationship into Coverage — the public release records this as a planned cross-domain capability rather than a live relationship. Ownership changes (transfer/resale of a private vehicle) is labeled Planned for the same reason: acquisition and retirement are modeled, a full ownership-transfer chain is not yet.

Evidence & limits

Scope and known limits

Early decades are reconstructed; ownership evidence is contextual, without a precise city stock split. The refreshed Nairobi release reports passing realism checks, with fleet scale near the reference band’s lower edge. Visible samples are semantic illustrations, not captured live queries.

Evidence, findings and release history 2 documented sections
Known limits.

Known limits.

Early decades are reconstructed; ownership evidence is contextual, without a precise city stock split. The refreshed Nairobi release reports passing realism checks, with fleet scale near the reference band’s lower edge. Visible samples are semantic illustrations, not captured live queries.

Read the published detail

Direct route-, trip- and vehicle-registration evidence does not extend back to the 1940s–60s for Nairobi. Those early decades are reconstructed rule-by-rule from the historical model, with fares, fees and operating assumptions scaled well below present-day levels. The page therefore treats early-period detail as calibrated history rather than literal observed records.

Transport models Nairobi's commercial mobility ecosystem rather than every registered vehicle in the city. Published registration evidence is therefore used as context, while private and institutional vehicle ownership is handled by the Vehicles domain. The Transport release does not claim a city-specific ownership split where no authoritative Nairobi benchmark is available.

certification check previously warned that the modeled PSV/matatu fleet sat below the cited real-world range of roughly 11,000–20,000 vehicles. In the 2026-08-04 Transport results, the modeled fleet is 11,364 vehicles and the realism check passes. It remains close to the lower edge of the evidence band, so the page continues to show the benchmark rather than implying false precision.

Earlier occupancy behavior did not distinguish time-of-day strongly enough. Nairobi was refreshed and re-certified after the correction; the current release reports all Transport realism checks passing. Exact formula changes are controlled.

The visible sample is a representative semantic record rather than a captured live-query result. This limitation applies only to presentation and does not imply that the certified Transport population is absent.

View all Transport limitations →

View Full Transport Change Log →

Evidence and assumptions.

Evidence and assumptions.

Review the reference sources and calibration periods.

Read the published detail

Baseline era. No direct vehicle-registration data exists this far back for Nairobi — reconstructed rule-based, with fares and fees scaled to a small fraction of present-day levels.

Urban expansion and deregulation. Kenya's matatu sector traces to the 1973 Kenyatta-era deregulation that broke the earlier KBS-era monopoly — the origin of the SACCO/individual-operator structure still modeled today.

Safety regulation era.

Institutional formalization. Kenya's NTSA was formed in 2012 (Act No. 2000) were both operating at scale.

Contemporary calibration threshold. Fare, fee, occupancy and licensing assumptions transition to modern operating levels, providing the anchor used by later generated trips and fleet economics.

The 2026-08-04 Nairobi Transport review covered driver age, lifetime chronology, employment and congestion relationships, and transfer patterns. All 22 structural and all 10 realism checks passed in that review.

Published registration, regulatory and field-research evidence used to anchor Nairobi's transport history, fleet scale and institutional milestones.

Values computed from observed evidence rather than copied directly — for example, normalized rates and city-scale operating ratios used by calibration.

Fleet scale, route activity, operating patterns and mobility behavior are calibrated to cited transport evidence and release-level checks. Exact operating weights and assignment parameters remain controlled.

Individual synthetic assignments are generated under controlled domain rules. Exact sampling, assignment order and parameterization are not published.

View Transport Evidence Catalogue →

Access & datasets

Scope your data request

Choose the records, dates and connected domains you need. Final availability, delivery scope and licensing are agreed with your quote.

Published access and recorded examples 2 documented sections
Explore this domain.

Explore this domain.

Available as Standalone Domain · Multi-Domain Bundle · Full City Twin™

Recorded example.

Recorded example.

Published release reference · These recorded checks are not a current rerun.

Explore the supplied synthetic example and its source references.

Read the published detail

Citizen 703282, Nairobi. Two published synthetic PassengerJourney rows, 20 minutes apart, connected by a transfer at the same stage.

KES 65.00, paid by Mobile.

KES 45.00, paid by Cash — the second leg, boarding 20 minutes after the first alighted, at the same stage.

Explore This Record →