3.9 Measuring Forces
45
3.9 Measuring Forces
In physics, forces are experimentally determined by measuring the trajectories of
particles, especially changes in their speed and direction of motion. It would be
natural to do this for pedestrians, too. At the time when we developed the social force
model for pedestrians, I could not imagine that it would ever be possible to measure
social forces experimentally. But a few years later, we actually managed to do this. In
around 2006, the advent of powerful video camera and processing technologies put
my former Ph.D. student, Anders Johansson, into the position to detect and analyze
the trajectories of pedestrians from filmed footage. Using this data, we adapted the
parameters of the social force model in such a way that it optimally reproduced
the trajectories of the observed pedestrians.
36 In 2006/07, similar tracking methods
became essential for the analysis of dense pedestrian flows and the avoidance of
crowd disasters.
37
Later, in 2008, Mehdi Moussaid and Guy Theraulaz set up a pedestrian experiment
in Toulouse, France, under well-controlled lab conditions.
38 This finally allowed us to
perform data-driven modeling. While before, we had to make assumptions about the
functional form of pedestrian interactions, it then became possible to determine the
functional dependencies directly from the wealth of tracking data generated by the
pedestrian experiment. After fitting the social force model to individual pedestrian
data, it was finally used to simulate the flows of many pedestrians. To our excitement,
the computer simulations yielded a surprisingly accurate prediction of the pedestrian
flows observed in a wide pedestrian walkway.
So, pedestrian modeling can be considered a great success of sociophysics.
One can say that, over time, pedestrian studies have turned from a social to a
natural science, bringing theoretical, computational, experimental and data-driven
approaches together. This has even led to practical and surprising lessons for the
design of pedestrian facilities and for the planning of large-scale public events such
as the annual pilgrimage in and around Mecca, as we will discuss below.
3.10 Most Pedestrian Facilities Are Inefficient
Back in 1994/95, Peter Molnar and I compared a range of different designs of pedestrian facilities. Surprisingly, we found that obstacles, if properly placed, can make
pedestrian counter-flows more efficient (see Fig. 3.5). In fact, all of the conventional
design elements of pedestrian facilities such as corridors, bottlenecks, and intersections turn out to be ill-designed and can be considerably improved! In many cases,
“less is more” in the sense that providing less space for pedestrians can produce a
36 Johansson et al. [22].
37 Johansson et al. [23].
38 Moussaïd et al. [24].
45
3.9 Measuring Forces
In physics, forces are experimentally determined by measuring the trajectories of
particles, especially changes in their speed and direction of motion. It would be
natural to do this for pedestrians, too. At the time when we developed the social force
model for pedestrians, I could not imagine that it would ever be possible to measure
social forces experimentally. But a few years later, we actually managed to do this. In
around 2006, the advent of powerful video camera and processing technologies put
my former Ph.D. student, Anders Johansson, into the position to detect and analyze
the trajectories of pedestrians from filmed footage. Using this data, we adapted the
parameters of the social force model in such a way that it optimally reproduced
the trajectories of the observed pedestrians.
36 In 2006/07, similar tracking methods
became essential for the analysis of dense pedestrian flows and the avoidance of
crowd disasters.
37
Later, in 2008, Mehdi Moussaid and Guy Theraulaz set up a pedestrian experiment
in Toulouse, France, under well-controlled lab conditions.
38 This finally allowed us to
perform data-driven modeling. While before, we had to make assumptions about the
functional form of pedestrian interactions, it then became possible to determine the
functional dependencies directly from the wealth of tracking data generated by the
pedestrian experiment. After fitting the social force model to individual pedestrian
data, it was finally used to simulate the flows of many pedestrians. To our excitement,
the computer simulations yielded a surprisingly accurate prediction of the pedestrian
flows observed in a wide pedestrian walkway.
So, pedestrian modeling can be considered a great success of sociophysics.
One can say that, over time, pedestrian studies have turned from a social to a
natural science, bringing theoretical, computational, experimental and data-driven
approaches together. This has even led to practical and surprising lessons for the
design of pedestrian facilities and for the planning of large-scale public events such
as the annual pilgrimage in and around Mecca, as we will discuss below.
3.10 Most Pedestrian Facilities Are Inefficient
Back in 1994/95, Peter Molnar and I compared a range of different designs of pedestrian facilities. Surprisingly, we found that obstacles, if properly placed, can make
pedestrian counter-flows more efficient (see Fig. 3.5). In fact, all of the conventional
design elements of pedestrian facilities such as corridors, bottlenecks, and intersections turn out to be ill-designed and can be considerably improved! In many cases,
“less is more” in the sense that providing less space for pedestrians can produce a
36 Johansson et al. [22].
37 Johansson et al. [23].
38 Moussaïd et al. [24].