Passenger demand and transport service analytics system

The planner compares actual trips, ticket usage and passenger flows. See where the data is measured and where the demand is yet to be adjusted.

Ticket and boarding records are considered to be the total passenger traffic, although there is a lack of data for exits, transfers or failed journeys. The overall average hides an overcrowded section or mistakenly justifies reducing the service.

How the solution works

  1. Matched day-to-day voyages, actual execution and assigned usage signals.
  2. The analyst checks which trips have sales and passenger counting data and which records can duplicate.
  3. The stream is examined by time and route section, distinguishing the values assessed.
  4. The planner compares the options for frequency or transport capacity according to service requirements and execution costs.
  5. The result of the approved change is assessed in conjunction with passenger service and data limits.

Key challenges

  • Capabilities are planned from over-general demand data

Solution capabilities

Background to the actual service

A journey that has not taken place, shortened or replaced shall be separated from the scheduled supply.

Alignment of flow sources

Ticket sales, their checks, passenger counters, and manual observations are analyzed based on what each source really measures.

Segments and Time Analysis

Specific travel points and periods are assessed. Actual filling is not derived from boarding alone, when the exit or other required ground is missing.

Capability scenarios

The frequency, capacity or schedule is compared to the identified need, transfers, minimum service level and real resources.

Verification of the result of the change

Comparison separates a schedule change from a season, event, or other significant external difference.

Business context

Capabilities are planned from over-general demand data
Ticket and boarding records are considered to be the total passenger traffic, although there is a lack of data for exits, transfers or failed journeys. The overall average hides an overcrowded section or mistakenly justifies reducing the service.
Transport supply is measured by specific flows
It is important for the passenger to have the right trip and enough space in time for it. Analysis of route sections and time allows to determine where common averages hide the need. Changes are assessed based on the actual service and reliability of the data while maintaining agreed service objectives.

Core features

  • Background to the actual service
  • Alignment of flow sources
  • Segments and Time Analysis
  • Capability scenarios
  • Verification of the result of the change

Key integrations

Sources of tickets and validity checks
Ticket sales and usage data with product rules applied to them.
Trip management
Real execution, transport assignment, cancellation and route change.
Sources of passenger computation
Boarding, disembarkation and other measurements are recorded, indicating their accuracy and the locations where they were collected.
Schedule and service planning
Valid plan, service requirements and approved change.

Potential impact (%)

The ranges indicate an illustrative relative change in the metric under the stated assumptions. Results depend on the starting position and actual use of the solution. Percentages for different metrics must not be added together.

Service Planning Analysis Work

12–36%Decreasing

This illustrative scenario assumes that 30-60% of manual data entry and handover work can be addressed. That share is assumed to fall by 40-60%. Company data is needed to verify both the addressable workload and the resulting change.

The analyst's active preparation time is compared for reviews of equal length of routes and periods.

Unestimated passenger capacity mismatch

5–25%Decreasing

This illustrative scenario assumes that 20-50% of missed actions can be identified through task and deadline tracking. That share is assumed to fall by 25-50%. Company data is needed to verify both the addressable share and the resulting change.

Properly measured sections of non-conformity shall be monitored before and after the approved change, while maintaining comparable conditions.

Share of travel requests that are suitable for passenger demand

1–3%Increasing

Sample starting portion - 70%. Assumption: 10-25% of the remaining cases relate to the schedulers' still unmatched voyage time or capacity; a solution would help resolve 15-30% of these cases.

Queries with the correct departure time and accessible location are divided by all collected comparable travel demand requests. Evaluated after a schedule change implemented, separating seasonality.

Conditional calculation scenarios. The assumptions have not been validated against client measurements.

When this solution is relevant

  • Average trip occupancy does not show overcrowded sections or places where passenger computation data is missing.
  • The timetable change is proposed by sales, with no real-life travel being agreed.

Implementation requirements

Planned and completed journeys and locations where passenger flows are measured are agreed upon. Events, learning days and disruptions are marked separately. Capacity is measured by comparing similar sections of the route and reliable data.

Further development options

  • Forecasts of seasonal flows, with clear indication of available measurements and missing sections
  • A capacity change test on a selected route and a comparison of its service result

Frequently asked questions

Adapting the solution to your business