Social Distancing

The measures taken to contain Covid 19 infections have brought public life to a standstill and many restrictions to everyday life. The good news is that these measures are now beginning to take effect, allowing a gradual return to some sort of normalcy. However, there is a risk that once restrictions are relaxed, infection rates will immediately shoot up again. 

Technologies from the AIT Austrian Institute of Technology can help ensure that this does not happen. This is because simulations can be used to test the effectiveness of measures even before they come into force and thus filter out the optimum variant from several possibilities. A central question here is: How can the most important measure of all - keeping a minimum distance of one meter to and from the next person - be ensured when stores and parks are now increasingly opening again? "Especially in public places where we are on foot, such as transport infrastructures (train stations, subway stations, trains, etc.), essential local supply stores (supermarkets, drugstores, pharmacies, etc.) or parks, larger crowds can occur that exceed the available spatial capacities" explains Stefan Seer, researcher at the AIT Center for Mobility Systems. While it is not easy to change the structural design, it is possible to shape the use of buildings and public spaces.

"The movements of people as individuals, in groups, or even in crowds are dynamic, making it difficult to predict what implications different actions will have," Seer said. But with modern simulation systems, it is possible. Seer's research team has developed a solution called SIMULATE for this purpose, in which flows of people in public spaces and the behavior of pedestrians in defined environments are simulated. This can also be used to analyze the consequences of various organizational or construction measures: For example, one can vary the number of people in a space, virtually change culverts, provide one-way streets and detours, or close certain paths. In this way, it is also possible to estimate how long people will be close to each other and for how long. 

One example of this is the design of transfer nodes in public transportation: By cleverly changing the access to platforms, the use of escalators or sidewalks when transferring, the contact times of passengers (i.e., the time in which they come closer to people than one meter) can be greatly reduced - namely from the previous average of 50 seconds to less than five seconds. And this is achieved without increasing transfer times or dwell times in the station examined by means of simulation. 

Such simulations are also highly relevant in supermarkets and other stores. There, too, there are numerous possibilities for directing the flow of people in such a way as to minimize the contact time of customers. Such measures can be implemented quite easily in some cases: Customer frequency, for example, can be regulated by the number of shopping carts and baskets available - those without a cart have to wait outside the store until one becomes available. One-way streets and barriers can be implemented using belts, such as those found in waiting areas at airports. 

In an exemplary simulation of customer flows in a supermarket, it was assumed that customer frequency was halved and a one-way system was in place in the store - with no change in the time customers spent in front of the shelves. The status quo without these measures was that virtually no person in the clientele had less than three minutes of contact (less than one meter apart) with another. When the measures were implemented, on the other hand, contact time was drastically reduced: almost two-thirds of customers had less than ten seconds of contact with others, and 90 percent had less than 30 seconds. Seer concludes, "Our simulation can both support the efficiency of current interventions and examine strategies for their effectiveness and potential risks when habitual activities in daily life are gradually reinstated."

Figure 1: Simulation of the passenger flow of a subway station (a) without measures and (b) using measures to split the passenger flows (circles represent people; red circles signal people whose distance to the nearest person is less than 1 meter).

Simulation of customer flows in a supermarket (a) without measures and (b) using measures to split flows (circles represent people; red circles signal people whose distance to the nearest person is less than 1 meter).