TANGENT
Enhanced data processing techniques for dynamic management of multimodal traffic
Mobility & logistics
Artificial Intelligence
https://tangent-h2020.eu/ ←Back to Research projects
Sector
Mobility & logistics
Capability
Artificial Intelligence - Artificial Intelligence
Research focus UD
Ecological transition
https://tangent-h2020.eu/
Financing
Goals
TANGENT project aims to develop new complementary ICT tools for optimising traffic operations in a coordinated and dynamic way from a multimodal perspective and considering automated/non-automated vehicles, passengers and freight transport. TANGENT will allow the precise knowledge and management of the mobility flows among the transport modes and will enable the implementation and integration of innovative mobility solutions, services and business models.
How is it achieved?
TANGENT will research on advanced modelling and simulation techniques, such as: prediction and simulation models to identify future transportation demand and supply; optimization techniques to balance the flows of demand between the different means of transport; and the modelling of users’ travel behaviour.
TANGENT will deliver a set of applications for decision-making support creating a framework for coordinated traffic and transport network management, encompassing an enhanced mobility information service API and dashboard. The services will deliver real-time traffic management recommendations and will support transport authorities in designing optimal strategies for the entire transport network, for that, real time information and preductive information on the transport network will be handled. Different hypothetical scenarios will also be addressed in which different response plans will be studied.
TANGENT will tested in the cities of Rennes, Lisbon, Manchester and Athens.
What was our contribution?
At Deusto we lead research on the transport network optimization using Artificial Intelligence techniques, which aims to support transport authorities in making decisions at a strategic and tactical level. The module will use the current state of the traffic, as well as the predictions and simulations of the future evolution of the traffic to determine the best possible actions that can be taken according to the restrictions and the scenarios considered by the transport operators. The restrictions refer to aspects such as the capacity of the entire transport system, the maturity of the digital infrastructure, the adaptability of the transport offer, environmental conditions, etc. Among the management strategies are traffic control, balancing transport demand, incentives for the use of public transport.
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement Nº 955273
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