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Technical University of Crete
Country: Greece
110 Projects, page 1 of 22
  • Funder: EC Project Code: 235931
  • Funder: EC Project Code: 833915
    Overall Budget: 2,495,500 EURFunder Contribution: 2,495,500 EUR

    Traffic congestion is a serious threat for the economic and social life of modern societies as well as for the environment, which calls for drastic and radical solutions. The proposal puts forward an utterly original idea that leads to a novel paradigm for vehicular traffic in the era of connected and automated vehicles (CAVs) and is based on two combined principles. The first principle is lane-free traffic, which renders the driving task for CAVs smoother and safer, as risky lane-changing manoeuvres become obsolete; increases the static and dynamic capacity of the roadway due to increased road occupancy; and mitigates congestion-triggering manoeuvres. The second principle is the nudge effect, whereby vehicles may be "pushing" (from a distance, using sensors or communication) other vehicles in front of them; this allows for traffic flow to be freed from the anisotropy restriction, which stems from the fact that human driving is influenced only by downstream vehicles. The nudge effect may be implemented in various possible ways, so as to maximize the traffic flow efficiency, subject to safety and convenience constraints. TrafficFluid combines lane-free traffic with vehicle nudging to provide, for the first time since the automobile invention, the possibility to design (rather than merely describe or model) the traffic flow characteristics in an optimal way, i.e. to engineer the future CAV traffic flow as an efficient artificial fluid. To this end, the project will develop and deliver the necessary vehicle movement strategies for various motorway and urban road infrastructures, along with microscopic and macroscopic simulators and traffic management actions. TrafficFluid risk stems from the immense challenge of designing a new traffic system from scratch; however, we expect that the project will trigger a whole new path of international innovative research developments and testbeds that would pave the way towards a new efficient traffic system in the era of CAVs.

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  • Funder: EC Project Code: 321132
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  • Funder: EC Project Code: 249217
  • Funder: EC Project Code: 752094
    Overall Budget: 164,653 EURFunder Contribution: 164,653 EUR

    Today, particularly so in the face of climate change and the need to meet global food and water security requirements, there is an urgent need for a better understanding of natural processes in the Earth System and of land surface interactions (LSIs). The recent rapid developments in Earth Observation (EO) technology (new satellites launched, drones) demonstrate the real need and the true potential of this technology in this direction. In this context, ENviSION-EO proposes the implementation of cutting-edge modelling interventions to the SimSphere Land Biosphere Model (LSM) towards developing a 2D LSM tool that will allow deriving for the first time spatio-temporal estimates of key parameters characterising LSIs. Furthermore, the action aims to unravel the potential of an EO-based modelling technique, so-called "triangle", in deriving estimates of key parameters characterising LSIs from EO data acquired from ESA's (Sentinel-3) and unmanned aerial vehicles (UAVs). Another aspect of ENviSION-EO lies in elucidating the potential of the "triangle" technique in downscaling existing global operational products of SSM provided today at a meso-scale-resolution using Sentinels-3 data. ENviSION-EO proposes to undertake ground-breaking research that will lead to the development of innovative modelling methodologies, LBM tools and EO-derived products. It is anticipated that these will greatly increase our capability to model LSIs at multiple, previously unattained, observation scales, and provide important information for both new research and practical applications. Furthermore, the multifaceted and novel developments of ENviSION-EO together with the capacity and track record of the host organisation and the supervisor in training researchers at the MSCA level ensure a holistic development of the applicant to a scientist with a unique set of skills and expertise in EO Modelling of LSI's globally. Dr. George P. Petropoulos is the applicant fellow.

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