Madison Square Garden opened in 1968. Its seats have been upgraded, its screens replaced, and its concessions modernized. Yet the building itself remains largely the same. The concourses are still narrow, the entrances are still where they have always been, and the exits still funnel into the same surrounding streets. But the people moving through those spaces are entirely different.
If you were to model crowd movement from thirty years ago and compare it to today, the results would be unrecognizable. The venue has not moved. The crowd has.
In our upcoming webinar, we will bring this to life through simulation. Before we get there, it is worth understanding what is driving the difference.
Crowd modeling began in the 1970s with the work of John Fruin, whose book Pedestrian Planning and Design defined how architects and engineers understood people in motion. Fruin’s formulas linked density, speed, and flow, and his famous “human body ellipse” helped designers estimate how much space a person truly occupies when walking. These principles still form the basis of many simulation tools today, including MassMotion, which is the crowd simulation technology used by SimWell.
But Fruin’s world was different. He modeled pedestrians before smartphones, bag checks, and rideshare zones existed. The physical laws of motion remain the same. The behaviors driving them have changed completely.
The biggest shift in pedestrian dynamics has come from the small screens in our hands. Multiple studies show that phone use changes how people walk. Distracted pedestrians move about 10 to 20 percent slower and stray more from center paths. They also make more abrupt stops to check messages, take photos, or reorient themselves.
In isolation, these changes seem minor. In dense crowds, they compound quickly. A few people slowing down can ripple backward through hundreds of others, creating temporary blockages that never would have existed in earlier decades. Fruin’s model captured predictable flow under ideal conditions, but modern crowds no longer move that way. Any realistic model must now account for the interruptions and behavioral randomness created by mobile devices.
Modern events do not start at the door. They start at the security line.
Security screening has become a permanent variable in crowd dynamics, one that fundamentally alters how and when people reach their seats. Event security is now a $12 billion industry, and even efficient systems introduce new friction. Every checkpoint changes the rhythm of arrival and redistributes congestion across the site.
Fans now expect to queue, but those queues often form in spaces never designed for extended waiting. To model that process accurately, planners need to capture not only how people move but also how they stop and how long they stay there.
Arrival patterns have also shifted.
Parking once dictated how people entered a venue. Today, many arrive by rideshare or drop-off zones clustered along the curb. The shift creates new intersections of cars, scooters, and pedestrians, often just steps from the entrance. Studies show pedestrians slow by five to ten percent in rideshare zones, adding friction just outside entrances.
Traditional pedestrian flow models assumed large, synchronized arrivals from public transit or parking lots. Rideshare arrivals are the opposite: smaller, continuous streams that peak differently and create unexpected surges near pickup points after an event.
Crowds also leave differently. People used to walk directly to their cars or the train. Now they wait — for drivers, friends, and curb availability. Those extra minutes of dwell time keep plazas, lobbies, and sidewalks occupied long after the event ends, shifting when and where congestion appears. For most venues, curb management now matters as much as entry design. The curb has become the new front door.
In 2019, SimWell CTO André Jacques built a crowd model using the standard parameters that defined pedestrian design at the time: arrival curves, capacity, density, and flow. It reflected the assumptions planners used before phones, security screening, and rideshare zones began reshaping how people move.
For this webinar, we asked André to recreate that scenario using today’s behavioral data. The software has always been capable of capturing these dynamics, but they were not yet the main drivers of crowd behavior. Now they are.
André applied the same modeling principles and inputs, updating them to account for modern variables such as phone distraction, checkpoint delays, and curbside dwell time. The result reveals how crowd movement patterns change when human behavior evolves, even if the physical parameters stay the same.
During the session, André will share how he updated the model in MassMotion, what he learned in the process, and how you can apply the same approach to your own projects. The differences are measurable, visual, and immediate.
Architecture evolves slowly. Behavior evolves every season.
The past few years have changed how people move through familiar spaces, and those shifts now define how planners must think about safety, flow, and design readiness.
Simulation brings those differences into focus. It allows us to test how the same parameters perform under modern behaviors and to see exactly where friction, delay, or opportunity appear.
Join us for “Rethinking Event Traffic: Modern Crowd Simulation with MassMotion.”
You will see how small behavioral changes add up to measurable differences in crowd flow and learn how to model them yourself with MassMotion.