Reduce economic and social disparities
Strengthening Bilateral Relations
Through the EEA Grants and Norway Grants, Iceland, Liechtenstein and Norway contribute to reducing social and economic disparities and to strengthening bilateral relations with the beneficiary countries in Europe.
The three countries cooperate closely with the EU through the Agreement on the European Economic Area (EEA).
For the period 2009-14, the EEA Grants and Norway Grants amount to €1.79 billion. Norway contributes around 97% of the total funding. Grants are available for NGOs, research and academic institutions, and the public and private sectors in the 12 newest EU member states, Greece, Portugal and Spain. There is broad cooperation with donor state entities, and activities may be implemented until 2016.
Key areas of support are environmental protection and climate change, research and scholarships, civil society, health and children, gender equality, justice and cultural heritage.
The “COOD Matrix” project of Goal Systems has been one of 101 projects selected in the second call. The European institution is betting on this project due to the success of its original achievements in the R+D, significant improvement in the energy efficiency field, industrial investigation or the experimental development along with the professional history and technological capacity of Goal Systems to tackle such a complex project.
Transport modelling tools are essential for optimal transportation planning and designing services to passenger demand in public services of different sectors (i.e. bus, metro, tram, suburban, etc.). Mathematical prediction models combined with proper analysis of specific necessities within each case, extraordinary help while deploying a new transport system or when increasing quantity and quality of the commercial offer.
GOAL SYSTEMS’ COOD Matrix project
Optimized Generation of Commercial Offer in Transport Systems based on Origin-Destination Matrix
Designed to create and develop a planning tool for automatic and optimum generation of the commercial offer of multi-modal transport systems. It will be based on origin destination matrices of passenger demand.
Statistical passenger flow data allows the creation of origin-destination matrices (OD matrix) of passenger demand, which are a schematic representation of all existing flows between nodes in the network. Today, there are tools capable of translating the demand matrix into routes and trip frequencies, minimizing the transport time of the passengers. However, many of these planning solutions are inefficient or unusable in its go-life process, since they do not take into account the legal / business / operation rules and preferences.
In addition, planning solutions within railway or BRT (Bus Rapid Transit) systems have to manage special features imposed by the network topology such as blocking, overtaking maneuvers, train arrival maneuvers at stations, etc. High mathematical complexity and deep knowledge of the sector problems are the two critical facts that explain the lack of enhanced tools on the market.
Focusing the research on artificial intelligence algorithms, heuristics definition, and combinatorial optimization, the experienced members of the Project team will create an innovative tool that fully compliments and integrates within other transport planning applications, and consequently brings a dramatic increase in efficiency to transport systems.
Results of the Research
The result of the research carried out in this project is a new model which allows the algorithm to decide during the calculation the itinerary of the commercial trips of the vehicles on the transport network.
This model creates an itinerary which is adapted to the offer, using the passenger demand matrices (origin-destination) as a starting point.
The project is focused on the most critical and technically complex aspect, satisfying the quality criteria of the transportation companies.
The new representation model of the transport network adapts better to the problem of itinerary coordination in common stretches.
Goal Systems’ algorithm is the only one capable of using this model to build, during the calculation, the itineraries of the vehicles that fit best the demand.
The result is always optimal trips at every moment depending on the passenger demand.
The vehicles circulating through a stretch belonging to many lines decide the itinerary to be followed by each vehicle when arriving to a fork.
Thanks to Goal Systems heuristics, the number of trips of each branch corresponds to the desired frequency.
By using the method of micro-simulation of operations in the transport network, the scheduling solutions built avoid lacks of other tools, whose solutions are not viable and cannot adapt to changes because they have been built without considering the operation details of the company.
These decision steps to assign an itinerary to a vehicle as part of the calculation are new and improve even more the optimization obtained with Goal Systems’ products.
