Leading Theme Park Operator
Balancing Express and Standby Queues in Real Time
A leading theme park operator used Safari AI to predict wait times, track ride dispatch and fill rate, and set the express-to-standby merge ratio at its attractions.
Measured from existing queue and station cameras
Express and standby lines were balanced by feel at the merge point.
Where a ride's express and standby queues met, a team member decided how many guests to let through from each. Without live data, express guests waited longer than they paid for, or the standby line stalled while seats went empty.
- Merge ratios were set by eye, not by measured queue lengths
- Posted waits were estimated from heuristics and manual counts
- Fill rate and dispatch gaps only showed up in end-of-day reports
Wait times, dispatch and merge guidance from one live feed.
Connected to queue and station cameras via an on-premise server
Existing queue and ride station cameras fed a lightweight on-premise server Safari AI deployed in the park, so video was processed on site.
Measured queues, merges and every dispatch
Computer vision counted guests in the standby and express queues, time-stamped every dispatch and measured the fill rate of each one.
Guided the merge point in real time
A traffic-engineering model told merge staff how many guests to admit from each queue, and predicted waits updated for guests across the park.
Note: Illustrative data
Shorter standby lines, and express that stays express.
Predicted waits were updated from measured queue data, so guests choose rides with accurate expectations and staff can spread the crowd.
Merge staff got a measured ratio for every attraction, so express guests keep the speed they paid for without stalling standby.
Dispatch timing and fill rate were tracked ride by ride, so empty seats and slow loading get fixed during the peak.
Action Center: From Insight to Action.
Measurements like these feed Safari AI's Action Center, which turns a drifting merge ratio or a slow dispatch into a specific staff action.
- Real-time recommendations to improve KPIs via email, SMS, robocall, mobile app, Power BI, or API.
- Recommendations grounded in your own written SOPs, not generic best practices.
See this on your own attractions.
This operator balanced express and standby queues with live measurements from cameras already in its parks. We'll walk through which attractions and merge points are the best fit for a pilot on your cameras.
