Internship position at INRIA Sophia Antipolis (France) EPIs OPALE and OASIS Funded by EIT KIC ICT Labs:
“Intelligent adaptive transport systems”
OPALE specific part:
Macroscopic traffic flow models allow describing the spatio-temporal evolution of traffic density. Their sound mathematical structure consisting of partial differential equations of hyperbolic type and the related efficient numerical schemes enable fast computations to monitor traffic evolution. The selected candidate will apply these models to detect and/or predict problematic situations and offer (almost) real time solutions. The numerical schemes are programmed in Matlab and on the C++ platform Num3sis (see http://num3sis.inria.fr/), and could, if necessary for the aim of this internship, be re-programmed in Java. The goal of the internship is not primarily to design, program, such equations, as some numerical codes already exist. However, given the competencies of the selected candidate, it can be envisioned to also contribute in designing and programming new numerical codes.
OASIS specific part:
Input data injected within such predictive numerical computations and the resulting output will be taken and provided as events. Indeed the main goal of the internship will be to succeed to connect the numerical computations with a sophisticated platform, named PLAY.
PLAY platform has been designed by the EU funded STREP project PLAY (see http://play-project.eu). Its role is to collect events, semantically described using web-semantic standards (e.g. the RDF format), reason upon these events by combining them thanks to a Complex Event Processing (CEP) engine, thus producing new (complex) events. The new events have also to be described in RDF. Events can be delivered to interested third-party, which are usually services, which have subscribed to such events (topic and content-based subscriptions). Thus third-party end services get the possibility to react, adapt to some relevant events describing some specific situation that have been detected by PLAY.
The original aspect of the subject is to combine a relevant traffic evolution model with a platform (PLAY) for events processing capable to gather and generate events about a specific situation happening in the context of transportation, more precisely in the context of multi-modality transportation (i.e. mix of public transportation, pedestrian, car, bicycle, etc) . These events will not only be generated through the specific transportation-related complex event processing rules (deployed at the CEP level, e.g. to suggest the most suited transportation mode at a given point in the journey), but will also result from on-demand calculations of the numerical schemes which will enrich the overall traffic management with the detection or even prediction of problematic traffic situations (yet in a single transportation mode).