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CEGUM

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Coordination for Efficient and Green Urban Mobility

Traffic hotspots in Europe are expected to generate over 203 billion Euro of economic cost by 2025. Traffic congestion in cities raises serious concerns on the level of CO2 emissions, fuel consumption and discomfort to drivers due... ver más

31/05/2021

SINTEF

214K€

Presupuesto del proyecto: 214K€

Líder del proyecto

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-05-31

MSCA-IF-2018: Individual Fellowships

I+D

Cerrada hace 6 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

SINTEF

214.16K€ | Lider

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Duración del proyecto: 24 meses Fecha Inicio: 2019-05-02
Fecha Fin: 2021-05-31

Líder del proyecto

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 214K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Traffic hotspots in Europe are expected to generate over 203 billion Euro of economic cost by 2025. Traffic congestion in cities raises serious concerns on the level of CO2 emissions, fuel consumption and discomfort to drivers due to prolonged travel time and large idle time behind the red lights. Unnecessary acceleration and deceleration towards traffic junctions can also highly contribute to extensive use of fuel, increase in emissions and engine and brake wear. Current traffic signal control approaches are not adequate for tackling the problem because they focus on traffic flow efficiency and disregard the individual drivers’ interests. The aim of this project is to develop a method that does not only coordinate all the traffic signals in an urban network, but also takes the vehicle speeds in to account and effectuates a coordination between the traffic lights and vehicle speeds alike. Such a coordination will make the most of the infrastructure and technological developments for reaching an efficient, eco-friendly, and safe urban mobility. Due to the complexity and stochastic nature of the traffic system, the coordination problem will be addressed by integrating model-based distributed control techniques with reinforcement learning-based algorithms. Comprehensive analysis and benchmarking will be performed to obtain a complete evaluation of the idea and prove its effectiveness in improving urban mobility with respect to different indices like fuel consumption, CO2 emissions and number of stops. Adaptive cruise control systems already installed in a large number of cars in European countries. Automakers are announcing the marketing of autonomous cars in the coming years. Soon European cities should be ready to make the most of these technological developments to provide more efficient, cleaner and safer urban mobility and this project is a strong step towards this direction.

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