Date:
Friday 10th July 2020 - 12:00 to 12:20
Venue:
INI Seminar Room 2
Abstract:
Interaction
based risk - an agent based analysis of London
We have seen
unprecedented changes in transport demand and supply, as a result of Covid-19.
Transportation can play a key role in the regional economic recovery by
enabling people to safely access work, healthcare, education. But we know that
Covid-19 is highly contagious, and there are no current vaccines. Transport
agencies will need to plan safe services that minimise crowding, maintain
critical service schedules, and mitigate new challenges as operating resources
are pinched.
Established
transportation modelling techniques are not designed to analyse how individuals
travel, at a granular level. This makes it challenging to estimate how changes
in transport demand (the result of physical distancing policies) may impact
public transport and identify where coronavirus transmission risk may be
greatest. Agent based models (ABMs) provide granular insight into how
individuals behave. The aggregate consequences of individual behaviours can be
analysed to understand where and when congestion may happen, which populations
make use of which public transit services, and other network-wide consequences.
Arup has been working
with TfL to understand how public transport may impact the risk of Covid-19
transmission in London. We have extensive experience in developing ABMs –
including an ABM for London, developed as part of a previous, collaborative
TfL-Arup research initiative. We have been testing a new epidemiological model
in conjunction with our London mobility ABM that attempts to take into account
"virus infection dynamics" (EpiSim , developed by Technische
Universität Berlin).