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X-Machines for Agent-Based Modeling: FLAME Perspectives
FIGURE 9.3: Part of a Concoursia simulation of a London main station.
It might be useful to have heat maps and other outputs to understand
the situation better.
In terms of planning activities, the system can be used to understand the
impact of retail activities on passenger behavior, such as how passengers
interact with shops? Not every visitor is travelling, so the impact of passenger behavior on retail potential is of interest. Is the retail potential
of the transport hub maximized by the location and mix of retail activities (are the shops in the right place)? The impact of flows generated
by retail activities can be studied? Are they compatible or conflicting
with flows related to the main function of the airport as a transport hub
with associated stations, bus stands, car parks etc.? It is common for
temporary exhibitions/events to be placed on the concourse, so what
is their impact on pedestrian flow? What are the best dates/times for
them to be held? (Figure 9.5)
There has been much recent research on how people behave in environments. It can predict what people will do in timescales from 10 minutes
to several hours. This is based on either direct feeds from sensors or historical data. It can be used to test out scenarios or interventions so that
managers can understand what the best strategy is. In Concoursia, each
individual is simulated within the building and predict their movements.
Information can be presented in many ways and managers can use this
for
• Planning new developments
• Dealing with changes to the layout of the airport
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