Modelling Crowd Movements

Catching up with the investment that is required to address a backlog of transport infrastructure upgrades is a global issue, and the ball is mainly in the politicians’ court. Meanwhile, engineers working on the transformation of Toronto’s downtown Union Station are proving that the profession is ready and able to play its part, managing changes to a multi-modal transport hub with minimal disruption. The station is the main terminus for the GO regional rail network, a connection into the city’s streetcar and subway networks, plus a gateway into the PATH system of walkways.

While the original design work is done, the project team has had to grapple with the logistical challenges of staging construction in a way that minimizes disruption and maximizes the safety of users. The station handles over 30,000 passengers during the morning peak hour and more than 250,000 over a typical business day. It is because these numbers are expected to more than double over the next 10 years, with up to 70,000 passengers during the peak morning rush hour in 2021, that getting the Union Station project right is so crucial.

When the project master plan was adopted in 2004, Arup was awarded the contract to assess the pedestrian flows through the station during the refurbishment and for the predicted conditions of 2021. The study revealed a number of opportunities and constraints for the refurbishment, and it informed the best locations of the retail, commercial and transit-related facilities. The modeling analyzed the 2021 predicted passenger flows, and also checked each stage of the refurbishment to ensure that the station would continue to function while the rebuilding work closed off parts of the concourses.

MassMotion modeling to avoid construction chaos

The planning study used MassMotion modeling for 3D pedestrian simulation. MassMotion, was developed by Oasys, the software house of Arup, to fill a gap in the capabilities offered by other programs. The 3D environments are easily imported from standard CAD tools such as AutoCAD Revit, architectural drawings, or imported direct from BIM models.

The platforms and station were modeled in detail, while the network of adjacent streets and walkways were modeled within the same file in a more abstract fashion. Thereafter, the speed and scalability of MassMotion enabled the engineers to test and optimize ideas. For instance, by adjusting stair, retail and service locations, the team was able to improve the balance of pedestrian flows as well as the user experience.

The speed of iteration in MassMotion is now proving useful in supporting the construction staging. While high-level planning was done on the drawing board before contractors even got near the site, no-one could really predict what was going to happen on site. The same tool that was used for overall master planning is giving rapid turnaround during construction to ensure that any impacts will not cause chaos in rush hour.

To be really successful as a planning and management tool, pedestrian modeling must be as near to real life as possible. MassMotion’s pedestrian models are based on industry standard planning and design guidelines for pedestrian behaviour. But these models are then easily calibrated against actual observed flows and adjusted so that the analysis is consistent with each specific project and location.

Program agents react in a dynamic environment

MassMotion pedestrian simulation is also different in that it models pedestrian behaviour rather than testing a designer’s preconceptions. The individual agents in a MassMotion simulation make their own choices about appropriate actions, based on the dynamics of their environment and how their actions affect other agents. For example, if the interface between rail and subway has several portals, other pedestrian simulation tools require the designers to make a subjective decision and input what percentage of the population in the space will use each portal. In a MassMotion simulation each agent decides which door to use based on what it knows about the distance to its goal and how long the queue is for each door and how much time they are prepared to invest in the interchange. “In a multi-modal hub like this, getting the interchanges right is critical if we are to achieve the vision of truly integrated transportation,” says Morrow.

MassMotion agents need to be assigned an origin and a destination. They then navigate their own way through the environment and will respond dynamically to congestion and queues. This means that the more complex an environment becomes, the quicker it is to set up or modify the model. What a MassMotion agent knows can even be tailored to suit different cultures, for instance allowing for people’s tendency to give way to the left or right.cce

Erin Morrow is product director of the MassMotion crowd simulation and analysis tools developed by Oasys Software, a part of Arup Group. Morrow, a member of  the Canadian Institute of Planners and American Institute of Certified Planners, is based in Arup’s offices in Toronto. For more information, see www.oasys-software.com/massmotion