Phd Position, Orange Labs, Belfort
Forum 'Emplois' - Sujet créé le 2010-08-30
PhD Topic: Mobility Models from Radio Mobile Network Measures
Term: 3 years
Place: Orange Labs' premises in Belfort (East of France)
Date Posted: 08/30/2010
Validity: 1 month
To apply: send statement of research interests & your resume at th-resa-net-ops@rd.orange-ftgroup.com
Description:
Urban organization, which includes housing as well as employment or leisure, requires increasing exchanges between different density areas. Mobility has thus become a key element within the society. Understanding mobility is a major issue in which all stakeholders involved in land planning (network constructions, business settlement, etc), land organization (transport planning, etc) or land management (pricing policy, regulation, etc) activities work.
As study contexts of mobility are very diverse, there are a lot of different mobility models, which were designed to be implemented in specific areas. People mobility can be represented as stochastic. This approach provides an insight into people commuting dynamics, but it cannot study a specific individual. Another approach takes into account the fact that a person commutes based on his target and his environment. Individual travels can thus be represented in a very precise manner. In both of these approaches, the input data are based on results of surveys conducted with a representative cross-section of the population that commutes.
The outline of this study is to use location information of mobile phone network users to complete such surveys with a dynamic approach. Mobile phone network can gather very significant volumes of information which are frequently updated. This information can be obtained in real or delayed time in order to determine a more or less rough estimate of mobile phone network users' location.
The objective of this PhD is to propose, based on information obtained by the mobile phone network, a methodology to develop people mobility models which can be widely applicable to the entire population and take into account behavior modifications according to the social economic and geographic context.
Users' location information is by nature spatially and temporally scattered. The challenge is then to extrapolate the information in order to describe as real as possible the entire population displacements (trajectory analysis, areas of interest, flows, etc).
These extrapolated data will then fuel existing mobility models. Depending on the application, these models highlight general dynamics of a population (macro mobility) or the movement of individuals (micro mobility).
desired skills for the PhD:
- Architecture of mobile networks, protocols (signaling data)
- Theory of surveys, statistics, data-mining, missing data processing
- Stochastic processes, differential equations, Markov chains, etc
- Multi-agent systems, cellular automata, etc
Term: 3 years
Place: Orange Labs' premises in Belfort (East of France)
Date Posted: 08/30/2010
Validity: 1 month
To apply: send statement of research interests & your resume at th-resa-net-ops@rd.orange-ftgroup.com
Description:
Urban organization, which includes housing as well as employment or leisure, requires increasing exchanges between different density areas. Mobility has thus become a key element within the society. Understanding mobility is a major issue in which all stakeholders involved in land planning (network constructions, business settlement, etc), land organization (transport planning, etc) or land management (pricing policy, regulation, etc) activities work.
As study contexts of mobility are very diverse, there are a lot of different mobility models, which were designed to be implemented in specific areas. People mobility can be represented as stochastic. This approach provides an insight into people commuting dynamics, but it cannot study a specific individual. Another approach takes into account the fact that a person commutes based on his target and his environment. Individual travels can thus be represented in a very precise manner. In both of these approaches, the input data are based on results of surveys conducted with a representative cross-section of the population that commutes.
The outline of this study is to use location information of mobile phone network users to complete such surveys with a dynamic approach. Mobile phone network can gather very significant volumes of information which are frequently updated. This information can be obtained in real or delayed time in order to determine a more or less rough estimate of mobile phone network users' location.
The objective of this PhD is to propose, based on information obtained by the mobile phone network, a methodology to develop people mobility models which can be widely applicable to the entire population and take into account behavior modifications according to the social economic and geographic context.
Users' location information is by nature spatially and temporally scattered. The challenge is then to extrapolate the information in order to describe as real as possible the entire population displacements (trajectory analysis, areas of interest, flows, etc).
These extrapolated data will then fuel existing mobility models. Depending on the application, these models highlight general dynamics of a population (macro mobility) or the movement of individuals (micro mobility).
desired skills for the PhD:
- Architecture of mobile networks, protocols (signaling data)
- Theory of surveys, statistics, data-mining, missing data processing
- Stochastic processes, differential equations, Markov chains, etc
- Multi-agent systems, cellular automata, etc