• Expression of Interest

    AI for Real Time Green Map for Smart Mobility. (GREEMO).
    green mobility; smart mobility; zero emission; real time energy map; eco-routing; eco-driving; deep learning; artificial intelligence; intelligence transportation system.

    The main objective of the project is to use the ICT in the field of green mobility in order to reduce EV energy consumption and TV GHG emission. In fact, the use of ICT constitutes a vital challenge for connected EV while waiting for better battery life, better availability of charging stations and better charging time. It is also essential for connected TV while waiting for the zero GHG emission transition. As vehicles will become more and more communicating, the idea of this project is to observe continuously driving profiles and vehicles parameters, inter alia, real EV energy consumptions and real TV GHG emissions. These data will be collected by the vehicular cloud and merged with other information (infrastructure, road traffic, weather conditions, etc.) with the aim of offering drivers instructions for eco-driving and eco-routing while respecting the usual instructions of security.

    ESIGELEC (France) as a lead partner.

    The project request the following expertise: 

    • Computer vision and embedded systems
    • Mobile robotics
    • Deep learning based EV energy consumption modelling
    • Deep learning based VT GHG emission modelling
    • Energy map development-based Machine learning
    • Multi-objectives/ criteria optimisation approaches for eco-routing
    • Deep learning-based eco-driving model
    • Computer vision, environment perception algorithms-based deep learning
    • Autonomous navigation for smart mobility
    • Securing communication and data trust management

     

    We need in our Project:

    • Academic research laboratory
    • SMEs
    • Big company in Automotive or Embedded Systems or TIC
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    ESIGELEC has been developing for decades European and international collaborations in various fields related to embedded systems, mobile robotics, electronics, automation and information and communication technologies. ESIGELEC and its researchers combine their skills in embedded systems for autonomous and connected mobile systems (computer vision for perception, localization and autonomous navigation, data security and trust management, machine an deep learning), electronics, automation and computing and carry out solid and recognized scientific activities developed along several axes: Smart mobility, EMC and reliability of components and systems, radio frequency and microwave circuits (design, modelling and characterization), and system fault tolerance control (robust control, diagnosis/prognosis and estimation).