Information Technology Reference
In-Depth Information
Fig. 5.
Rose-like graph of frequencies for 12 outbound service calls at the evening peak: each
route is represented by a triangle illustrating its direction and relative frequency
In order to infer the patterns of transit volumes in each direction per time of day
(on average), may be worth using clustering analysis, e.g. putting in evidence similar
directional service patterns among different time intervals. In these cases, the use of
colored “graph-image” may be useful (Figure 6).
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4 8 1 0 1 0 1 0 1 0 9 8 6 4 4 5 6 6 6 5 4 5 5 7 8 8 9 1 0 1 0 9 8 8 7 6 6 3 3 3 3 2 1
6 7 8 9 10 11 12 13 14 15 16 17 18 19 2 0 2 1 2 2 2 3 2 4
time
Fig. 6.
Average inbound and outbound public transit volume by direction and time of day (30
min clusters)
The ODSS uses GIS technology by integrating the Google Maps service that al-
lows the representation of geo-referenced information on a map. So, the graphical
visualization of a particular day run, for a particular vehicle, is displayed in Figure 7.
Green points represent pick up points and red points represent drop off points (or
both, if there is anyone to pick up there).
Fig. 7.
Routes of a vehicle during a particular day
