Urban Micro-Mobility Fleet Usage

This dataset contains granular trip-level logs for urban micro-mobility fleets, including vehicle, user, location, timing, and operational details. It enables robust analysis of mobility patterns, peak demand periods, and operational efficiency, supporting data-driven decisions for city planners, fleet operators, and sustainability initiatives.

  • last updated 26 Jan 2026
  • by GoMask
The brief that made it

Peak demand and usage pattern analysis for urban planning

Sample rows

preview · 8 of 150 rows · all 21 columns
trip_idstringweather_conditionstringtrip_duration_minutesfloatoperational_issue_flagbooleanpayment_typestringvehicle_idstringvehicle_typestringuser_idstringtrip_start_datetimedatetimetrip_end_datetimedatetimestart_latitudefloatstart_longitudefloatend_latitudefloatend_longitudefloatdistance_kmfloattrip_costfloatstart_zonestringend_zonestringis_peak_periodbooleanbattery_level_startintegerbattery_level_endinteger
TRX1001clear20falsecredit_cardVEH001e-scooterUSR001A2024-06-01T07:14:002024-06-01T07:34:0035.6895139.691735.694139.70724.27.5ShinjukuIkebukurotrue9681
TRX1002cloudy23falseprepaidVEH002bikeUSR002B2024-06-01T12:23:002024-06-01T12:46:0037.7749-122.419437.7811-122.42372.73.9DowntownCivic Centerfalseblankblank
TRX1003rain35falsemobile_walletVEH003e-bikeUSR003C2024-06-01T17:45:002024-06-01T18:20:0051.5074-0.127851.501-0.14195.89.7WestminsterSohotrue8974
TRX1004clear15falseotherVEH004otherUSR004D2024-06-01T08:14:002024-06-01T08:29:0048.85662.352248.86272.351.92.5Le MaraisChâtelettrueblankblank
TRX1005windy1truedebit_cardVEH005e-scooterUSR005E2024-06-01T18:02:002024-06-01T18:03:0034.0522-118.243734.0523-118.24380.20.8Arts DistrictLittle Tokyofalse9191
TRX1006cloudy15falsecredit_cardVEH006e-bikeUSR006F2024-06-01T09:44:002024-06-01T09:59:0040.7128-74.00640.7306-73.98663.15.2TribecaEast Villagetrue8780
TRX1007clear3falseprepaidVEH007bikeUSR007G2024-06-01T10:34:002024-06-01T10:37:0052.5213.40552.521813.40970.71.2MittePrenzlauer Bergfalseblankblank
TRX1008rain30falsemobile_walletVEH008e-scooterUSR008H2024-06-01T19:26:002024-06-01T19:56:0041.8781-87.629841.8892-87.6275610.1The LoopRiver Northfalse8365

What the 150 rows show

from the 150-row sample

Other (weather condition) stands out: 12 of its 12 rows have operational_issue_flag = true, against 11 of 138 for the rest.

  • 15%operational_issue_flag = true
  • 21.0median trip_duration_minutes
  • 4vehicle types
  • 4.5median distance_km
  • 5.7median trip_cost
  • 88median battery_level_start
Operational issue flag rate by weather_conditionoperational_issue_flag = true
0%50%100%5%clear2 of 418%rain3 of 4022%snow2 of 99%cloudy3 of 337%windy1 of 15100%other12 of …
trip_duration_minutes150 rows, in bands of 10
0357023236321745310050100trip_duration_minutes →

Median 21.0, from 0.02 to 80.0.

payment_type150 rows · 5 values
  1. prepaid40
  2. credit_card39
  3. mobile_wallet32
  4. debit_card23
  5. other16
21 columns by typefrom the column list below
  • string 8
  • integer 2
  • float 7
  • datetime 2
  • boolean 2

Columns

21 columns in four groups
blueprint · 21 columns
columntypedescriptionexample
Text 8 columns
trip_idstringUnique identifier for each micro-mobility tripuniqueTRX1001
vehicle_idstringUnique identifier for the vehicle used in the tripVEH001
vehicle_typestringType of micro-mobility vehicle (e.g., e-scooter, e-bike)e-scooter · e-bike · bike · othere-scooter
user_idstringUnique identifier for the user taking the trip (anonymized)USR001A
payment_typestringPayment method used for the tripcredit_card · debit_card · mobile_wallet · prepaid · othercredit_card
start_zonestringCity-defined zone or neighborhood where the trip startedoptionalShinjuku
end_zonestringCity-defined zone or neighborhood where the trip endedoptionalIkebukuro
weather_conditionstringGeneral weather condition during the trip (e.g., clear, rain, snow)6 values · optionalclear
Numbers 9 columns
trip_duration_minutesfloatTotal duration of the trip in minutes0 or more20
start_latitudefloatLatitude of the trip start location-90 to 9035.6895
start_longitudefloatLongitude of the trip start location-180 to 180139.6917
end_latitudefloatLatitude of the trip end location-90 to 9035.694
end_longitudefloatLongitude of the trip end location-180 to 180139.7072
distance_kmfloatTotal distance traveled during the trip in kilometers0 or more4.2
trip_costfloatTotal cost charged for the trip in local currency0 or more7.5
battery_level_startintegerBattery level percentage of the vehicle at trip start (0-100)0 to 100 · optional96
battery_level_endintegerBattery level percentage of the vehicle at trip end (0-100)0 to 100 · optional81
Dates and times 2 columns
trip_start_datetimedatetimeDate and time when the trip started2024-06-01T07:14:00
trip_end_datetimedatetimeDate and time when the trip ended2024-06-01T07:34:00
True or false 2 columns
is_peak_periodbooleanIndicates if the trip occurred during a defined peak demand periodtrue
operational_issue_flagbooleanIndicates if any operational issue was reported during the tripoptionalfalse

Use it for

  • operational is…15%23 of 150 rowsmean trip duration mi…21.6clear25.9rain14.9snow27.7clou…

    A transportation dashboard

    The operational_issue_flag rate, trip_duration_minutes by weather_condition and a breakdown of payment_type. Excel, Power BI or Tableau.

  • Why do 23 of 150 rows have operational_issue_flag = true?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable trips with vehicle_id, vehicle_type and user_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 21 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

10,000 rows of yours: $12.99One-time. No subscription. All prices

This dataset150 rows21 columns
Yours10,000 rows21 columns

blueprint · urban-micro-mobility-fleet-usage

Behind this dataset

Same schema. As many rows as you need.

These 150 rows came out of a blueprint — 21 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row represents a single trip for an e-scooter or shared bike.
  • Trips must include anonymized start/end geolocation, duration, and distance.
  • Fleet vehicle ID and vehicle type must be recorded for every entry.
  • Trips are only included if initiated in permitted city zones.
  • Maintenance flag is set if a vehicle required intervention post-trip.
Rows
Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
urban-micro-mobility-fleet-usage

More in Transportation

Browse all
Also in TransportationUrban Fleet Carbon Footprint LogTransportation Fleet Energy ConsumptionVehicle Fleet DataAll 1,947 datasets

What should your data show?

Preview 20 rows free
No signup. No card.