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TRIMIS

ENHANCED DATA PROCESSING TECHNIQUES FOR DYNAMIC MANAGEMENT OF MULTIMODAL TRAFFIC

Project

TANGENT - ENHANCED DATA PROCESSING TECHNIQUES FOR DYNAMIC MANAGEMENT OF MULTIMODAL TRAFFIC


Funding origin:
European
European Union
STRIA Roadmaps:
Connected and automated transport (CAT)
Connected and automated transport
Network and traffic management systems (NTM)
Network and traffic management systems
Other ()
Transport mode:
Multimodal
Multimodal
Transport sectors:
Passenger transport
Passenger transport
Freight transport
Freight transport
Duration:
Start date: 01/09/2021,
End date: 01/08/2024

Status: Finished
Funding details:
Total cost:
€4 849 349
EU Contribution:
€4 849 349

Overview

Background & policy context:

The European transport faces major challenges in terms of safety, greenhouse gas emissions, traffic congestion and its derived costs. In addition, the development of disruptive technologies and emergence of new mobility solutions generate a revolution in transport network and traffic management.

Objectives:

In this context, TANGENT aims to develop new complementary 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.

Methodology:

TANGENT will research on advanced techniques on modelling and simulation, such as prediction and simulation models for future demand & supply of transport; optimisation techniques for balancing the demand flows between the means of transport; and users travel behaviour modelling.

As result, a set of applications for decision-making support will be delivered creating a framework for coordinated traffic and transport management, encompassing an enhanced mobility information service and dashboard with associated APIs and advanced functionalities with a two-fold approach: to provide real-time traffic management recommendations and to support Transport Authorities to design network-wide optimal strategies. The framework also aims at supporting a multi-actor cooperation approach for transport network management by enabling communication channels. In this way, the services target to different actors in traffic management.

The results will be tested in three case studies: Rennes (FR), Lisbon (PT), Great Manchester (UK) and a virtual case study in Athens (HE) with real data from various modes of transport, under different traffic events such as bottlenecks, accidents, pedestrian flow etc.

The impact will be assessed to reach expected reduction targets of 10% in travel time, 8-10% in CO2 emissions, 5% of accidents, 5-10% increase in use public transport and use of active modes or 10% of economic costs due to a more efficient management.

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