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Public transport engineering data types and collection methods

Public transport engineering data types and collection methods
Boy or student getting on a municipal bus
© Wirestock / Envato

In the previous unit, we explored how CCTV analytic cameras can be used to generate traffic counts for traffic engineering projects. In this unit, we’ll shift our focus to public transport engineering data — how to measure it, analyse it, and use it to determine the capacity of a bus corridor.

By the end of this module, you’ll understand:

  • The different types of public transport data, including supply and demand data
  • Traditional and innovative methods for collecting passenger counts
  • How this data is used to calculate the capacity of a bus corridor

Let’s get started!

1. Types of Public Transport Engineering Data

Public transport data falls into two main categories: Supply data and Demand data.

Supply Data:

  • Bus fleet characteristics – Types and number of buses (standard, articulated, double-decker, etc.)
  • Service schedules – Frequency and hours of operation
  • Infrastructure details – Dedicated lanes, bus stops, and priority measures
  • Operational performance – Speed, reliability, headway (time between buses), and dwell time (at stops)

Demand Data:

  • Passenger counts – Number of people boarding and alighting
  • Ridership patterns – Passenger volume changes over time
  • Load factors – % of bus capacity used at various times
Accurate collection of both supply and demand data is essential to evaluating and improving public transport efficiency.

2. Methods of Collecting Passenger Counts

Passenger counts help transit planners understand demand and optimise services. Here’s how they’re collected:

Traditional Methods:

  • Manual Surveys – Staff count boardings/alightings at stops
  • Ticketing Data – Analysing ticket sales or fare records
  • Onboard Observations – Surveys conducted inside buses

Innovative Methods:

  • Automated Passenger Counting (APC) – Sensors and cameras on buses
  • Mobile Data Analysis – GPS and mobile phone location data
  • Smart Card Data – Contactless systems provide detailed ridership patterns (e.g. Week 2, Hong Kong)
Combining traditional and innovative methods ensures accurate and comprehensive data.

3. Using Data to Calculate Bus Corridor Capacity

Once data is collected, it can be used to calculate the capacity of a Bus Rapid Transit (BRT) corridor. This helps with:
  • Service optimisation
  • Infrastructure planning
  • Efficiency improvements
  • Investment justification
  • Sustainability efforts

Key Steps:

1. Determine Bus Capacity

Identify the number of seated + standing passengers per bus.

2. Calculate Bus Headway

Time between buses (in minutes).
> Shorter headways = more frequent service = higher capacity

3. Calculate Buses per Hour

Buses per Hour = 60 / Headway (minutes)

4. Consider Infrastructure and Speed

Dedicated lanes and signal priority = faster speeds and better flow.

5. Compute Load Factor

Average occupancy as a % of full bus capacity.

6. Calculate Corridor Capacity

Corridor Capacity = Bus Capacity × Buses per Hour × Load Factor

Example Calculation

  • Bus Capacity: 120 passengers
  • Headway: 5 minutes
  • Load Factor: 0.8 (80% occupancy)
  • Buses per Hour: 60 / 5 = 12
Corridor Capacity = 120 × 12 × 0.8 = 1,152 passengers/hour
Under these conditions, the BRT corridor can carry around 1,152 passengers per hour. Adjusting bus size, frequency, or load factor changes the outcome.

Conclusion

Public transport engineering relies on accurate data to improve transit systems. By:

  • Understanding supply and demand
  • Using effective passenger count methods
  • Applying data to calculate capacity

…transport planners can design services that are efficient, reliable, and sustainable.

See you in the next module!

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Data Fundamentals for Sustainable Mobility

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