DATA SIM Summer School on 'Mobility modeling and big data sources' (July 15-18, 2013) at Hasselt University

The Transportation Research Institute (IMOB) of Hasselt University organizes the first DATA SIM Summer School on 'Mobility modeling and big data sources'. The summer-school is aimed at both senior researchers, early-stage researchers, practitioners and (PhD) students in the domains of transportation sciences, data mining, behavioral modeling, activity-based travel demand analysis, agent-based-simulation and related topics.

LECTURES, GRADUATE SYMPOSIUM AND POSTER SESSIONS

This summer-school will feature a series of lecturers by renowned researchers in the field.

Furthermore, participants will have the opportunity to present their own work and get feedback during the graduate symposium sessions. Participants are encouraged to present their work in focus sessions supervised by a coach who is an expert in the field. Participants interested in presenting their work shall submit a 1 page (A4) abstract describing the main research objectives and methods used.

Finally, participants can exchange ideas with people in different focus groups, during one of the poster sessions.

CERTIFICATES

Participation Certificates will be issued to all participants of the summer-school.

TOPICS
1. Mobility modeling : basic principles and tools
1. Behavior modeling, activity based models (activity selection, planning,
daily schedule generation)
2. Multi-modal trips
3. Modeling cooperation, cooperative scheduling (e.g. carpooling)
4. Ontologies
5. Traffic and transportation related models, travel demand prediction models
6. Simulations in practice : what conclusions can be drawn ?
2. Special focus : Agent based modeling and simulation for : mobility, travel behavior,
mobility market, electromobility (including smartgrid), ...
1. Delimiting the domain of applicability : where can AgnBM be useful ?
2. Models for cooperation, mutual influence, negotiation
3. Computability issues, scalability
4. Ontologies
5. How to interpret results ? What can be expected ?
3. Big data as source for modeling
1. Big data repositories
2. Annotation, semantic enrichment of big data
3. Data mining and process mining to extract information from big data
4. Crowd sourcing and publicly available data : pitfalls and challenges
5. Using data from different sources : how to align ?
4. Integrating big data and modeling
1. Using big data to feed models or to validate model execution results
2. How to integrate semantically poor big data with small sets of semantically
rich data as input for microSimulation or agent based modeling ?
5. Applications
1. Electric vehicles (including smart grid concepts)
2. Carpooling (cooperation on trip traveling)
3. Multi-modality and car-sharing (cooperation on resource usage)
4. Markets based on big data related to traffic
1. Business models for EV, multi-modal trips, car-sharing, carpooling, ...
2. Online support systems (ride sharing advisors)
3. Traffic load prediction systems
5. Effect of EV characteristics (range anxiety, charging time, limited range) on
household travel behavior
6. Hot research topics in transportation behavior, traffic safety and logistics.

LOCATION
Hasselt University, Campus Diepenbeek, Agoralaan gebouw D, 3590 Diepenbeek Belgium

DETAILS - MORE INFO
http://www.datasim-fp7.eu/

CONTACT
luk.knapen@uhasselt.be