One of the central values at Shotl is that the data we collect is valuable for transport operators and city planners. That’s why, every Monday morning, we deliver a report with the most relevant KPIs of each operation from the previous week, this includes classification of demand by origin, destination and hour; average values of waiting and travelling time; etc.
Earlier this year we upgraded these reports with extra information, to visualise how a DRT operation reacts day by day. On the one hand, we have added daily graphs showing the occupancy of vehicles and its evolution by the minute. An example below:
In that graph, we can observe that the bus was principally used during the afternoon, especially on its peak (around 17:00). Although the maximum occupancy of the vehicle is 10 people, values over 5 were reached only twice during that day.
If that becomes a regular pattern, the operator and the city might know that running with a smaller vehicle would affect around that hour; this could help to reduce the operational costs significantly.
Furthermore, we plot the time that every passenger spends waiting and inside the vehicle and how this develops during the day. See the example below (taken from the same day as the previous graph):
Observing this data, we can notice that (a) the time that the passengers spend from confirming their bookings to pick up (waiting time) very rarely goes over 20 minutes, regularly remaining between 5 and 20 minutes; (b) the total time from pick up to drop off is often below 30 minutes; (c) these times get worse between 15:00 and 19:00, with a couple of extraordinary cases around 17:00.
This information is much more complete than general statistic values, whether they are average, median or quartile values. For example, an interested operator might consider compensating the two passengers from the “extraordinary cases” with a free trip.
Finally, the reports we share include a file attached, containing the raw data necessary to calculate them. Information is power, and at Shotl we believe that the best way to leverage it is by doing it jointly with our customers: the true owners of that data.
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