Simulating Cities: The Spacetime Framework
With the advent of alternative energy and the Internet of Things, there is suddenly a plethora of new technologies that will require major restructuring of cities. Some examples are autonomous vehicles, solar energy, unmanned aerial vehicles, and smart homes and buildings. In order to establish sound public policies, all these new technologies can greatly benefit from urban simulations, to measure their impact on the city and its people before the policies are defined.
Yet, despite all the reasons why complex simulations are desirable for decision and policy making, and despite advances in computing power, large distributed simulations of urban areas are still rarely used, with most of their adoption in military applications. The reality is that developing distributed simulations is much harder than developing non-distributed ones, and requires a much higher level of software engineering expertise, which usually modeling and simulation experts don’t have.
My students and I have been exploring how some of the ideas underlying Aspect-Oriented Programming can help overcome the design challenges faced by distributed simulations, as applied to urban simulations. There are many similarities between the concept of aspect (as given by AOP) and the general concept of “aspect of a city” that urban planning researchers routinely use. This talk looks at urban simulations from a socio-technical systems design perspective, and puts forward the idea that non-traditional decompositions are not just beneficial for these applications, but are likely the only way to develop realistic urban simulations. I will present a data-oriented framework that we are developing called the Spacetime framework, specifically designed for enabling large, collaborative, and decentralized simulations, and will show how it is being used in practice.
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