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Bus Data Ecosystem

1. Introduction​

Scope​

The dataset encompasses:

  • Standard GTFS components (Stops, Routes, Trips, Stop Times, Shapes, Fare Rules, Fare Attributes).
  • Additional datasets such as OD (Origin-Destination) flow for buses, operational schedules, and passenger boarding/alighting patterns.

Stakeholders​

Transit agencies, GIS teams, developers, urban planners, and researchers.

Use Cases​

  • Enhancing transit planning and operations management.
  • Supporting multi-modal transport integration and route optimization.
  • Developing real-time passenger information systems and analytics tools.

2. Categories and Data Fields​

Standard GTFS Categories​

1. Stops (stops.txt)​

  • Fields:
    • stop_id: Unique identifier (mandatory).
    • stop_name: Name of the stop (mandatory).
    • stop_lat, stop_lon: Geographic coordinates (mandatory).
    • location_type: Type of stop (e.g., 0 for stop, 1 for station).
    • parent_station: Reference to the parent station, if applicable.

Example:

stop_id,stop_name,stop_lat,stop_lon,location_type,parent_station
1001,Adarsh Nagar,28.7169,77.1703,0,

2. Routes (routes.txt)​

  • Fields:
    • route_id: Unique identifier (mandatory).
    • agency_id: Operator identifier (mandatory).
    • route_short_name: Short name or number (mandatory).
    • route_long_name: Full route description (mandatory).
    • route_type: Transport type (e.g., 3 for bus).

Example:

route_id,agency_id,route_short_name,route_long_name,route_type
2001,DTC,620,New Delhi to Dwarka,3

3. Trips (trips.txt)​

  • Fields:
    • trip_id: Unique identifier (mandatory).
    • route_id: Associated route (mandatory).
    • service_id: Service schedule identifier (mandatory).
    • trip_headsign: Destination or key stops.

Example:

trip_id,route_id,service_id,trip_headsign
3001,2001,1,Dwarka Sector 21

4. Stop Times (stop_times.txt)​

  • Fields:
    • trip_id: Associated trip identifier (mandatory).
    • arrival_time, departure_time: Timings (mandatory).
    • stop_id: Stop identifier (mandatory).
    • stop_sequence: Stop order in the trip (mandatory).

Example:

trip_id,arrival_time,departure_time,stop_id,stop_sequence
3001,08:00:00,08:00:00,1001,1

5. Shapes (shapes.txt)​

  • Fields:
    • shape_id: Identifier for the shape (mandatory).
    • shape_pt_lat, shape_pt_lon: Coordinates of shape points (mandatory).
    • shape_pt_sequence: Order of points (mandatory).

Example:

shape_id,shape_pt_lat,shape_pt_lon,shape_pt_sequence
4001,28.7169,77.1703,1

6. Fare Attributes (fare_attributes.txt)​

  • Fields:
    • fare_id: Unique identifier for the fare (mandatory).
    • price: Fare amount (mandatory).
    • currency_type: Currency code (e.g., INR).
    • payment_method: 0 (pay onboard) or 1 (prepaid).

Example:

fare_id,price,currency_type,payment_method
5001,10.00,INR,0

7. Fare Rules (fare_rules.txt)​

  • Fields:
    • fare_id: Fare identifier (mandatory).
    • route_id: Associated route.

Example:

fare_id,route_id
5001,2001

Additional Suggested Datasets​

1. OD Flow for Buses (od_flow.csv)​

  • Fields:
    • origin_stop_id: Origin stop identifier.
    • destination_stop_id: Destination stop identifier.
    • passenger_count: Number of passengers traveling.

Example:

origin_stop_id,destination_stop_id,passenger_count
1001,2001,350

2. Operational Schedules (schedules.txt)​

  • Fields:
    • route_id: Route identifier.
    • service_start_time, service_end_time: Operation hours.
    • frequency: Frequency of service in minutes.

Example:

route_id,service_start_time,service_end_time,frequency
2001,06:00:00,23:00:00,10

3. Boarding/Alighting Patterns (boarding_alighting.csv)​

  • Fields:
    • stop_id: Stop identifier.
    • boarding_count: Number of passengers boarding.
    • alighting_count: Number of passengers alighting.

Example:

stop_id,boarding_count,alighting_count
1001,120,90

3. Validation Standards​

Field-Specific Validation Rules​

  • Coordinates: Must be valid geographical values.
  • Identifiers: Must be unique and alphanumeric.
  • Times: Must adhere to HH:MM:SS format.

Cross-Category Validation​

  • Ensure route_id in trips.txt exists in routes.txt.
  • Validate stop_id in stop_times.txt against stops.txt.
  • Ensure trip_id in stop_times.txt exists in trips.txt.

4. Default Values and Tolerances​

  • Default missing location_type in stops.txt to 0.
  • Allow ±0.0001 for coordinate discrepancies.
  • For scheduled times, tolerate ±1 minute.

5. Example Data Templates​

Stops Template​

stop_id,stop_name,stop_lat,stop_lon,location_type,parent_station
1001,Adarsh Nagar,28.7169,77.1703,0,

OD Flow Template​

origin_stop_id,destination_stop_id,passenger_count
1001,2001,350