This code was written during the seminar "Service Analytics". The task was to simulate and review passenger arrival patterns, a major drawback was the absence of any data so the patterns could only be parametrued using parametersets from several research papers.
- Settings: line 150-165
- change Distribution type: line 164 + line 165
In this paper, we present the evolution of passenger arrival pattern modeling and the impact on waiting time for passengers of public transportation systems. First, we present the history of different approaches of modeling arrival patterns and the underlying distributions, elaborating specific advantages and disadvantages. Following, we present our simulation approach based on different probability distributions. In the simulation it was shown, that the relative waiting time decreases over an increasing headway. Even to a point, where the absolute waiting time decreases. Additionally, the effects of unpunctuality on the waiting time are simulated. Unpunctuality increases the averaged waiting time for all and especially for timetable dependent passengers. Resulting in the need for a reliable operation and real time updates for the schedule, so that the passengers can minimize their waiting time.