DATA SIM aims at providing an entirely new and highly detailed spatio-temporal microsimulation methodology for human mobility, grounded on massive amounts of big data of various types and from various sources, with the goal to forecast the nation-wide consequences of a massive switch to electric vehicles, given the intertwined nature of mobility and power distribution networks. While the increasing availability of big data about human activities provides radical new ways of understanding the social and ecological universe, it is our ambition in this project to complement this information with behaviourally rich data, pertaining to the purpose of human travels. In terms of interdependencies, our advanced integrated methodological environment allows for more realistic and consistent linkages across travel choices made by the individuals in the course of a day than conventional models, with the goal of simulating tens of millions of individual agents, each with their detailed prediction of every activity-travel schedule, enabling more detailed segmentations based on user profiles of the agents, different activity types, trip duration and driving ranges. Significant breakthroughs can be gained from the project, which lead to novel dimensions of use, along the milestones that were set forward in the European Industry Roadmap for the Electrification of Road Transport from today till 2020. Many scientists have already pointed out that the goal of social sciences is not simply to understand how people behave in large groups, but to understand what motivates individuals to behave the way they do. This fundamental insight, which can be gained from this project, is a step forward towards the solution of this important challenge, and it can help us to better understand the dynamics of our society and, in the longer run, to have an impact on overall and wider societal well-being.

DATA-SIM

MERELLI, Emanuela
2013

Abstract

DATA SIM aims at providing an entirely new and highly detailed spatio-temporal microsimulation methodology for human mobility, grounded on massive amounts of big data of various types and from various sources, with the goal to forecast the nation-wide consequences of a massive switch to electric vehicles, given the intertwined nature of mobility and power distribution networks. While the increasing availability of big data about human activities provides radical new ways of understanding the social and ecological universe, it is our ambition in this project to complement this information with behaviourally rich data, pertaining to the purpose of human travels. In terms of interdependencies, our advanced integrated methodological environment allows for more realistic and consistent linkages across travel choices made by the individuals in the course of a day than conventional models, with the goal of simulating tens of millions of individual agents, each with their detailed prediction of every activity-travel schedule, enabling more detailed segmentations based on user profiles of the agents, different activity types, trip duration and driving ranges. Significant breakthroughs can be gained from the project, which lead to novel dimensions of use, along the milestones that were set forward in the European Industry Roadmap for the Electrification of Road Transport from today till 2020. Many scientists have already pointed out that the goal of social sciences is not simply to understand how people behave in large groups, but to understand what motivates individuals to behave the way they do. This fundamental insight, which can be gained from this project, is a step forward towards the solution of this important challenge, and it can help us to better understand the dynamics of our society and, in the longer run, to have an impact on overall and wider societal well-being.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11581/332790
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