Objective
In traffic information centres data originating from roadside equipment and floating cars should be processed to recognize potential congestion and to suggest adequate routes. We would like to develop novel algorithms that optimize road system from the aspects of both the individual drivers and the whole system. We would like to apply methods, using graph theory and Integer Programming, which proved to work well in telecommunication networks and we intend to modify them considering the following factors: drivers' indeteinable behavior, drivers' reactions on guidance, and traffic characteristics. Heuristics will be developed (based on the idea of Simulated Annealing, Simulated Allocation, or Genetic Algorithm) for the cases when the optimal solution cannot be obtained in acceptable time. The effect of the algorithms will dynamically adapt to the current state of the network and also consider the future state of it, which will be predicted by using earlier stored data. The methods will be integrated in existing system architecture, and its effectiveness tested in a working system. In case of on-line operation the runtime of the algorithms are of crucial importance, thus it will be analyzed by complexity theory, by real scenarios and by simulations. The operation of the algorithms will be examined in existing pilot projects. The proposed research offers an excellent opportunity to widen both my view and knowledge towards traffic telematics and traffic control. The know-how and experience at the host institute and its international connections enable to obtain deep knowledge connected to practical observations. Pilot projects at Arsenal Research with FCD equipped taxis and other vehicles will enable to analyze and test the developed algorithms in practice and examine their behavior in complex systems. I would obtain experience how to participate in EU projects and after the fellowship I would be able to build up or participate in traffic telematics teams in Hungary, for which the need is continuously increasing. Innovative algorithms are expected that can be used in traffic information centres with enhanced network control and route guidance. Apart from the theoretical results a serviceable tool will be implemented. The practical benefits of these results are: higher capacity (throughput) of existing road systems; less traffic jams; and better route suggestions.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Topic(s)
Data not availableCall for proposal
Data not availableFunding Scheme
RGI - Research grants (individual fellowships)Coordinator
1030 WIEN
Austria