It is a very common approach for any business to analyze their historical sales records to adjust operation strategy.
Recently, Taiwan Railway Administration, a government-owned railway operator, faces serious competitions from other transportation systems.
It becomes very urgent for the operator to modify its timetables to meet demand patterns for increasing revenue.
The key issue is how to estimate passengers’ time-space characteristics.
For railroads with advanced automatic fare collection systems and simple service patterns, the estimation of passenger flow may not be difficult since detailed travel information is available. However, for systems with mixed traffic and insufficient ticket sales records, it requires a scientific method to deduce actual travel patterns from limited information.
This study tried to establish such a model to reconstruct the timespace distribution of passenger flow.
The model has been applied to Taiwan Railway Administration to estimate passenger flow.
The result is very useful for decision makers to assess the utilization of train capacities and to adjust service plans, such as adding/deleting train services, changing stopping patterns, or modifying service termini.
The proposed model can be applied to other railroads with mixed traffic operations and insufficient ticket sales records.
