Once you have built the skeleton of your Service and Zones, you need to define the kinds of riders that could theoretically access your service. From that, Realize can help you estimate the levels of demand on a given day.
Realize relies on the concept of ‘Demand Segments’ to generate demand estimates for your transportation simulation. A Demand Segment is a group of riders whose home or origin locations can be described with the same spatial Dataset. For example, if you have a Dataset that shows where all senior citizens reside in a city, you could build a Seniors Demand Segment from that dataset.
To create a Demand Segment, scroll down to the ‘Demand Model’ section of the right sidebar. Select your method of demand estimation from the dropdown menu: either ‘Predicted by Realize’ or ‘Manual Input’.
Next, scroll down to the Demand Segments table below. At first, it will be empty. Click on ‘Add Demand Segment’ to create your first Demand Segment. Note that you can create as many different Demand Segments as you wish; they will all appear in this table.
In the revealed sidebar, give your Demand Segment an informative name (e.g. ‘Senior Riders’, ‘General Microtransit Population’, ‘Paratransit Riders’).
From the ‘Dataset’ dropdown menu, select the corresponding Dataset that spatially describes the home locations of this Demand Segment. Only the Datasets that have data points located in your Service Zone(s) will show up in the dropdown menu. If the Dataset you need is not shown here, consider expanding your Zone(s).
The next step differs depending on whether you selected ‘Predicted by Realize’ or ‘Manual Input’ as the Demand Model in the previous sidebar.
If you selected ‘Predicted by Realize’, an Adoption Rate Slider will appear, which you can click and drag between 0% and 100%. The Adoption Rate describes the proportion of all trips in this Demand Segment that are taken using on-demand, once a service is introduced.
The Adoption Rate directly controls how many trips are assigned to different ‘Trip Types’ in the table below the slider. Realize estimates the relative proportions of different trip types (e.g. commuting, healthcare trips, entertainment and shopping trips, etc.) based on large travel surveys conducted across multiple continents. It then randomly generates origins and destinations of trips using the home locations of a Demand Segment and available Datasets corresponding to different Trip Types.
Note that as you change the Adoption Rate slider, Realize will recalculate the total number of daily trips in each row of the Trip Types table.
You can click on individual rows in the Trip Types table to view the temporal distribution of this Trip Type throughout a typical day. Two graphs are shown: an outbound distribution, which shows the times at which riders travel away from home to that particular activity, and an inbound distribution, which shows the times at which riders travel from the activity back home. Note that you cannot edit these temporal distributions in ‘Predicted by Realize’ mode.
If you’d like more control of the distribution of Trip Types, select ‘Manual Input’ as the Demand Model.
If you selected ‘Manual Input’ as the Demand Model, there will be no Adoption Rate slider, and the Trip Types table will initially be empty. Click ‘Add Trip Type’.
This takes you to a new sidebar allowing you to create a new Trip Type. Select your Trip Type from the dropdown menu. Realize presents you with a handful of key Trip Types that cover the majority of trips in most urban and rural areas.
Next, enter an estimate for the number of daily trips of this particular Trip Type that will be taken by this Demand Segment.
Navigate back to the previous sidebar, and repeat the steps above to populate your Trip Types table as necessary.