Data Sets
Dec 18, 2025
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Greater Kuala Lumpur Mobilities

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Authors
Gregory Ho Wai Son
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Key Takeaways
Data Sets Overview

A multi-year research project analyzing mobility patterns, public transport performance, and accessibility in Greater KL using large-scale administrative, geospatial and qualitative data.

gklmob
Data Sets
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Introduction

The Greater Kuala Lumpur Mobilities (GKLMOB) project is a multi-year research initiative examining how people move across the Greater Kuala Lumpur region, with a focus on public transport performance, accessibility, and user experience. The project integrates large-scale mobility data, administrative transport datasets, geospatial analysis, and qualitative interviews to build an evidence base for transport planning and policy reform.

A central component of GKLMOB is the analysis of bus system reliability and efficiency, including punctuality, headway regularity, and spatial coverage. This is complemented by qualitative interviews with public transport users to capture lived experiences of waiting times, comfort, safety, affordability, and convenience. Together, these quantitative and qualitative components aim to identify systemic barriers to mode shift and inform interventions to improve public transport outcomes.

Outputs from GKLMOB include datasets, technical notes, performance indices, policy briefs, and interactive data visualisations designed for policymakers, researchers, and the public.

Methodology

The dataset is constructed by integrating GTFS Static schedules with GTFS Realtime vehicle position feeds published by Rapid KL. GTFS Static data provides route, trip, and schedule definitions, while GTFS Realtime supplies high-frequency observations of bus locations and movement.

Vehicle position data are collected programmatically via the GTFS Realtime API. API calls are made every 15 seconds, on a daily collection window between 5:00 a.m. and 11:00 p.m., capturing operational bus movements during active service hours. Each API response is timestamped upon retrieval and stored as an individual vehicle position observation.

Raw vehicle position records include vehicle identifiers, geographic coordinates, and movement attributes such as speed and bearing.Vehicle positions are matched to scheduled trips using trip identifiers from the GTFS Static feed.

The resulting dataset supports analysis of bus movement patterns, service regularity, headway variability, and temporal–spatial performance metrics. The dataset represents vehicle-level operational data only and does not include passenger boarding, alighting, or load information.

Caveats

Data collection is limited to the 5:00 a.m. to 11:00 p.m. window and does not capture late-night or early-morning services operating outside this period.

GTFS Realtime data availability is dependent on the upstream API provided by Rapid KL. There are periods where the API was temporarily unavailable or unresponsive, resulting in short-term gaps in data collection.

Changes to the structure or schema of the GTFS Realtime feed occurred during the collection period. These changes required updates to the data ingestion pipeline and may have introduced gaps in the dataset, typically spanning several hours or, in some cases, multiple days.

Data gaps are not systematically imputed. Users should account for periods of missing data when conducting temporal analyses or aggregating statistics over time.

Vehicle position data reflects reported GPS locations and may be affected by signal loss, reporting delays, or device-level inaccuracies.

The dataset contains vehicle-level operational data only and does not capture passenger boarding, alighting, or load factors.

Metadata

Data Source(s) Rapid KL, GTFS static & GTFS realtime API
Last Updated 30th November 2025
Frequency Monthly
Format Parquet

Datasets

Rapid KL bus positions

Dataset Name

vehicle_positions

Dataset Brief Description

This dataset is derived from the General Transit Feed Specification (GTFS) Realtime feed for the Rapid KL bus service, obtained from Malaysia’s Official Open API. It contains raw GPS-based vehicle position records for Rapid KL buses operating on scheduled routes. Each row represents a single GPS ping from a bus at a specific timestamp, and each column is defined in the Columns section.

The dataset is updated monthly on YYYY/MM/DD and can be downloaded in Parquet format from the Download section.

Download Dataset

Download all 2025 data (ZIP)

Monthly downloads (2025)

Data Preview

Timestamp Trip ID Route ID Lat/Long Vehicle ID Bearing Speed Start Time
1735680581 weekday_U2000_U200002_0 U2000 3.245, 101.727 WVB4123 0 0.00 05:30:00
1735680601 weekday_U1800_U180002_0 U1800 3.193, 101.694 WVC4291 304 18.52 05:30:00
1735680613 weekday_U4210_U421002_0 U4210 3.144, 101.732 WVP2522 265.29 12.41 05:20:10
1735680600 weekday_U3000_U300002_0 U3000 3.134, 101.770 VFG2095 270.9 24.08 05:19:39
1735680611 weekday_U2000_U200002_0 U2000 3.246, 101.727 WVB4123 0 0.00 05:30:00
1735680609 weekday_U3030_U303002_0 U3030 3.132, 101.788 WVL734 32.4 27.78 05:30:09
1735680614 weekday_U2200_U220002_0 U2200 3.226, 101.744 WUU6711 218 25.93 05:30:14
1735680614 weekday_U2500_U250002_0 U2500 3.205, 101.732 WVD4028 310.1 20.74 05:30:14
1735680654 weekday_U4500_U450002_0 U4500 2.956, 101.792 VHB446 53.4 17.39 05:30:50
1735680631 weekday_U1800_U180002_0 U1800 3.195, 101.693 WVC4291 349 16.67 05:30:00

Column Defination

Timestamp Trip Info Route Coordinates (WGS84) Vehicle ID Bearing Speed (KM/H) Start Schedule
1735680581 weekday_U2000_U200002_0 U2000 3.24598, 101.72700 WVB4123 0.00 2025-01-01 | 05:30:00
1735680601 weekday_U1800_U180002_0 U1800 3.19328, 101.69417 WVC4291 304° 18.52 2025-01-01 | 05:30:00
1735680613 weekday_U4210_U421002_0 U4210 3.14449, 101.73299 WVP2522 265.29° 12.41 2025-01-01 | 05:20:10
1735680600 weekday_U3000_U300002_0 U3000 3.13409, 101.77093 VFG2095 270.9° 24.08 2025-01-01 | 05:19:39
1735680654 weekday_U4500_U450002_0 U4500 2.95669, 101.79215 VHB446 53.4° 17.39 2025-01-01 | 05:30:50

Rapid KL MRT Feeder bus positions

Dataset Name

vehicle_positions_feeder

Dataset Brief Description

This dataset is derived from the General Transit Feed Specification (GTFS) Realtime feed for the Rapid KL MRT Feeder service, obtained from Malaysia’s Official Open API. It contains raw GPS-based vehicle position records for MRT Feeder buses operating on scheduled routes. Each row represents a single GPS ping from a bus at a specific timestamp, and each column is defined in the Columns section.

The dataset is updated monthly on YYYY/MM/DD and can be downloaded in Parquet format from the Download section.

Bulk download

Download all 2025 data (ZIP)

Feeder Bus Vehicle Positions (2025)

Data Previews

Timestamp Trip ID Route Latitude Longitude Vehicle ID Bearing (DEG) Speed (KM/H)
1736327932 241209010218S12 T415 3.054465 101.786250 VAG4673 196° 1
1736327929 241209010013S12 T106 3.195752 101.610010 VG6519 152° 24
1736327922 241209010926S8 T401 3.111718 101.719480 VAG4729 16° 0
1736327930 241209010089S7 T114 3.214353 101.639540 VH1570 82° 0
1736327924 241209010205S11 T543 3.031315 101.677150 VX2864 155° 32
1736327917 241209010080S7 T817 3.136412 101.672640 VAF5750 33
1736327906 241209010112S9 T852 3.166052 101.664276 VAJ2895 77° 43
1736327912 241209010063S11 T418 3.136834 101.707720 VX2919 340° 13
1736327925 241209010030S11 T110 3.206914 101.616330 VH4985 130° 35
1736327913 241209010231S9 T807 3.128712 101.593710 VAJ9136 335° 0

Column Definitions

Column Name Data Type Description Valid Values / Units Example Value
timestamp datetime Timestamp of vehicle position observation ISO 8601 (UTC) 1746134878
trip_id string GTFS trip identifier GTFS-defined 250414010004S2
route_id string Vehicle route Alphanumeric T101
latitude float Vehicle latitude (WGS84) -90 to 90 3.206544
longitude float Vehicle longitude (WGS84) -180 to 180 101.616330
vehicle_id string Unique vehicle identifier from GTFS realtime Alphanumeric VH1568
license_plate string Reported vehicle license plate Alphanumeric VH1568
bearing float Direction of travel in degrees 0-360° 106
speed float Vehicle speed km/h 0
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