DATA SIM – DATA science for SIMulating the era of electric vehicles

(FP7, 2011-2014)

DATA SIM aims at providing an entirely new and highly detailed spatial-temporal microsimulation methodology for human mobility, grounded on massive amounts of Big data of various types and from various sources, e.g. GPS, mobile phones and social networking sites, 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. Significant breakthroughs can be achieved from this project, contributing to 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; 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.
The problems addressed by this project can be divided in two categories, the problem of data and the problem of models. The problem of data is associated with three crucial facts:
• Traditional diary surveys on travel behavior are a demanding and burdensome task for respondents, resulting in under-reporting of short trips and activities, poor data quality and falling response rates.
• The increasing availability of Big data represents a huge problem in terms of efficient data integration, data privacy and data storage.
• Big data lacks semantic interpretation, incapable of supporting the decisions of mobility and transportation management.
The problem of data models derives from the facts below:
• Current model structures and assumptions are too simple.
• Current used model outputs are insufficient.
• Current models and techniques are not scalable.
The objectives of the DATASIM project is
1. to tackle Big data challenges
2. to join Big data with behavioral motivation leading to truly novel social science laws
3. to set the behavioral sensitivity of the individual as the core entity in the novel simulation standard
4. to provide a novel standard for evaluation and benchmarking
5. to achieve scalability
The application scenario that is going to be investigated is the calculation of energy and mobility scenarios in the era of electrification of road transport. More specifically,
• Simulate millions of individual agents (nation-wide scale), each with its detailed prediction of activity-travel schedule, enabling more detailed segmentations based on user profile of the agent as well as behavioral adaption scenarios of current activity types, trip duration and driving ranges of the agent.
• Address the low voltage storage capability associated to millions of car batteries in charging mode as well as the capability of predicting mobility patterns for the batteries in usage mode, leading to the development of efficient energy management systems and an advanced charging infrastructure.
• Evaluate the amount of energy that is either required from or contributes to the electrified infrastructure, when mass production of plug-in hybrid and electric vehicles is fully established in Europe in about ten years from today.
Finally, Data Sim takes a pro-active approach and explicitly acknowledges data privacy as the main ethical issue.
1. Privacy is part of the project’s scientific core and addressed in an own work package WP1.
2. The collection and handling of all data is done according to the national legislation and recommendations, within the framework of:

• EU charter of fundamental rights
• EU directives on the protection of privacy 95/46/EC
• EU directives on the protection of privacy 2002/58/EC and amending acts
3. Steps taken to guarantee conformance to established data protection guidelines are documented.


UHasselt-IMOB Transportation Research Institute (IMOB) – Hasselt University web site
CNR Istituto di Scienza e Tecnologie dell’ Informazione “A. Faedo”
Italian National Research Council web site
BME Budapest University of Technology and Economics web site
Fraunhofer Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS web site
UPM Polytechnic University of Madrid web site
VITO Flemish Institute for Technological Research web site
Technion Israel Institute of Technology web site
UPRC University of Piraeus web site
HU University of Haifa web site


People involved: Despina Kopanaki, Nikos Pelekis, Yannis Theodoridis, Panagiotis Tampakis, Marios Vodas