The Auto-Assigner Metrics by Stop report builds on the existing Service Metrics by Stop report by including additional insights specific to Swiftly’s Auto-Assignment feature.
This report is ideal for operations and IT teams seeking to understand service reliability at the stop level and how Swiftly's Auto-Assigner assists agencies in capturing more service data.
What is Swiftly Auto-Assigner?
Assignment refers to matching an active vehicle to scheduled service. In cases where external assignment information about a vehicle is unavailable, Swiftly Auto-Assigner will intelligently match the vehicle's behavior to unassigned scheduled service.
If Swiftly Auto-Assigner was not active in these cases, this data would most likely be lost as unobserved or missing service.
For more detailed information, please refer the following help center article.
What’s Included?
This report includes all of the metrics available in the Service Metrics by Stop report, such as:
- Percentage of Observed Stops (pct_observed_stops)
- Number of Missing Stops that are explained via Service Adjustments (num_missing_stops_explained)
- Number of Missing Stops that are unexplained (num_missing_stops_unexplained)
In addition to this data, the Auto-Assigner Metrics by Stop Report introduces two new fields:
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Number of Stops Captured by Swiftly Auto-Assigner (num_stops_auto_assigned):
This metric counts the number of stop events (typically departures, but also includes arrivals if it is the last stop) observed by Swiftly while Auto-Assigner was active.
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Percentage of Stop Observations Captured by Swiftly Auto-Assigner (pct_stops_auto_assigned):
This is the ratio of auto-assigned stops to the total number of observed stops, expressed as a percentage (num_stops_auto_assigned divided by num_stops_observed, multiplied by 100). It reflects how frequently Auto-Assigner is used to capture stop events relative to all stop activity detected.
Below is an example of how this data can be leveraged to illustrate the impact of Swiftly Auto-Assigner:
Use Cases:
The report has filters on the left to select your download parameters. Below are several possible use cases for this report:
1. Understand the split of all scheduled stops given a time period to quickly evaluate how many stop events were captured using external assignment (e.g. a CAD/AVL feed), Swiftly Auto-Assigner, or are missing.
Group By: Empty to get it at the agency-level. (This is the default value)2. Evaluate Auto-Assigner usage by route or by stop to investigate service-specific trends in issues with underlying CAD/AVL systems
Group By: Route short name or select individual routes in the Route(s) dropdown.
3. Identify assignment issues at the vehicle level
Users can compare num_stops_auto_assigned or pct_stops_auto_assigned across the different vehicles reporting to Swiftly. This will enable users to easily find issues in their external assignment feeds for specific vehicle IDs.
Group By: Vehicle ID to identify a particular vehicle with a large volume of auto-assigned stops
4. Identify issues at the beginning of trips. Auto-Assigner is often used in the first few stops of a trip before an external feed has started to activate.
Group By: Route short name, Direction ID, and Stop ID to identify any issues with specific stops.
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