Dear colleagues,
Due to an overwhelming registrations for this event, we had to change the room. This event is taking place in Room G08, Chadwick Building, UCL, Gower St, London, WC1E 6BT (https://bit.ly/2Kshuli).
More information about this event can be found below:
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** Agent-based Modelling of Urban Transport Infrastructure -- Exploring the Impact of Urban Plans on Air Pollution in Beijing
** Dr Koen H van Dam (Imperial College London, UK)
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** Date and time: 30 November 2018 @4:00pm
** Location: Rm G08, Chadwick Building, UCL, Gower St, London, WC1E 6BT, United Kingdom
** Register here: https://ctsseminar-koenhvandam.eventbrite.co.uk
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Abstract:
To support operational as well as planning decisions for urban infrastructure, simulation models can be developed to test different scenarios, policies, technologies and designs against a range of key performance indicators. Agent-based models are particularly suitable for this as they can include the behaviour of a heterogeneous population and their impact on the environment. In this talk a case study in Beijing will be presented, comparing a range of possible redesigns for an urban area following the demolition of an old railway line which allows two neighbourhoods to be reconnected. By combining the simulation of daily activities for a given land-use plan and road network with detailed emission calculations, the impact on local air pollution generated from vehicle traffic can then be analysed for each scenario to provide decision-support for planners. To conclude, the potential for 3D semantic city models of cities to support such analysis will be shown.
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Biography:
Dr Koen H van Dam is a research fellow at the Department of Chemical Engineering, Imperial College London. He specialises in the development of simulation models of cities, in particularly related to energy, transport and water infrastructure. In recent projects he applied this approach to the water, sanitation and hygiene sector, electric vehicles, and local air quality. He is also interested in data infrastructures and how data can support decisions in smart cities.
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