Assigning Passenger Flows on a Metro Network Based on Automatic Fare Collection Data and Timetable

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/ddns/volume-2017/4373871/figures/4373871.fig.002a.svgz" name="4373871.fig.002a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>A single-route trip</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/ddns/volume-2017/4373871/figures/4373871.fig.002b.svgz" name="4373871.fig.002b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>A multiroute trip</td></tr></table>

<div>Frequency distribution of the observed travel times extracted from AFC data. The expected travel time of a route connecting a given O-D pair is based on average travel time. It can be estimated by the cluster analysis technique proposed in this paper.</div>

Discrete Dynamics in Nature and Society

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Figure 2

Figure 2: Assigning Passenger Flows on a Metro Network Based on Automatic Fare Collection Data and Timetable 