In the field of transportation, vehicles (ground or air) are becoming more and more autonomous and communicating. The emergence of these new technologies may relegate pilots to a supervisory role, implying less vigilance and less awareness of the environmental context. This degraded state can hinder the effective recovery of the vehicle and lead to dangerous situations. The objective of the COMMUTE project is to develop a genuine non-verbal, multimodal, intuitive and interactive communication system between the driver and his vehicle. For this purpose, multimodal solutions based on a cognitively situated approach will be developed within the framework of an interactive multimodal synthesis platform. Two use cases, presenting a strong safety issue, will constitute the common thread on which theoretical and experimental developments will be based: emergency warning (short time) and continuous regulation (long time).

In this project, we will investigate a new smart system made from a hardware component and a software approach that will enable the creation of programmable matter. The hardware component is a mass-producible, sub-mm, MEMS, namely a micro-robot using computationally controlled actuators used for power distribution, communication, adhesion, and locomotion. The software approach aims to provide a language enabling scalable, real-time, efficient, expressive and at the same time safe programming of an ensemble of micro-robots and making this ensemble interacting with others communicating things through the IoT. This research focuses on the main challenge to programmable matter: Scaling. For hardware the challenge is to scale down the size of the individual unit. For software the challenge is to scale up the number of elements that can be effectively controlled with a single, easy to understand program. Moreover, the simulation framework must scale up in the number of simulated micro-robots. We tackle the former by using a true 3-dimensional LSI/MEMS chip integration with deformable substrate as our main manufacturing method and a single effector, for all the necessary functionality of the unit. The latter is tackled creating Foxel a recursively scale-invariant functional shape description language implemented in a logic programming language, Meld, to create programs which are inherently concurrent, distributed, fault-tolerant, and also amenable to formal proofs. This project is a follow-up of the Claytronics project initiated by Intel and Carnegie Mellon University and then co-leaded with FEMTO-ST.

The STELLAR (SusTainable mEtaL fueLs for future trAnspoRtation) project intends to demonstrate the viability of new energetic carriers. Based on both energy and transportation sector requirements – such as autonomy related to weight or volume, easy refill, cost, distribution and storage – metal powders appear convenient as renewable alternative fuels. Indeed, they can burn to release heat without any carbon chemistry, and can be regenerated by thermochemical processes powered by renewable sources. This has the potential to create a major breakthrough in addressing renewable energy storage issues, climate change, and transport fuel costs, in accordance with mid-to long-term French government expectations. Promising recent studies performed by the project stakeholders mitigate the inherent risks that could be encountered by this breakthrough proposal in terms of targets and barriers. This works propose an distinctive approach to solve on the long term the energy storage and the climate change mitigation issues. This enhances STELLAR’s investigations to overpass a Technology Readiness Level 3. The project will aim to endorse several significant breakthroughs: capability to control the combustion of the particles so that the heat generated is practicable for a dedicated thermodynamic converter; designing of trapping on board 100% of the oxidized particles; and improving the processes to produce and regenerate particles using concentrated solar energy. Appropriate converters will be studied in order to match the specificities of the heat source with different transport applications. Furthermore, a life cycle assessment of the technology will position the concept in terms of Green House Gas emission, energy request and expected cost. The outcome of this multidisciplinary project will provide valuable answers to the major problem of energy storage and will serve as a basis for industrial developments in several key sectors (energy, automotive, aeronautics, metallurgy).

Three-dimensional bluff-body wakes are of key importance due to their relevance to the automotive industry. Such wakes contribute to consumption and greenhouse gas emissions. Drastic European Union limitations concerning these two mechanisms conduct the car industry to think about efficient vehicles. In this project, we propose robust drag and fuel reduction solutions for road-vehicles by closed-loop control of turbulent flows working efficiently for a range of operating conditions including changing oncoming velocity and transient side winds. To achieve this goal, we combine passive, active control and closed-loop strategies by using compliant deflectors, unsteady micro-jets and Machine Learning techniques. This project aims to prove a feasibility of the control from laboratory scale up to a full-scale industrial demonstrator. The main repercussions of the project will be on the reduction of the environmental impacts of transport industry and the gain of competitiveness and employment. This project consists on experiments in wind and water tunnels, numerical simulations and control strategies. Two models will be used, the square back bluff body and a reduced scale car model. The latter is representative of SUV and is inspired from the model used in collaborative work between POAES and PRISME. Control strategies will be tested in both configurations by combining passive and active actuation i.e. fixed or moving flaps and micro jet actuators. Closed-loop control will also be developed in these situations. Control strategies will be mainly developed by PPRIME. Experiments will be done in PRISME and PPRIME. LHEEA will take in charge numerical simulations and optimization. Finally, PSA will provide the vision of an automobile manufacturer on the industrial feasibility of the developed control strategies.

As part of research on advanced driving assistance systems (ADAS), the ICUB project aims at designing and developing a new vision based system able to detect road obstacles, even in critical situations like moving obstacles, presence of reflecting objects or puddles on the road, poor weather conditions or faraway obstacles. We propose in this project a consistent system that includes all necessary steps from data acquisition to the targeted detection. Regarding the imaging system, it will involve a stereo-polarimetric head. Obstacle detection will be implemented through multimodal fusion of polarimetric data and disparity map, as provided by stereovision. The main objective of multimodality is to leverage jointly fine scale discrimination of detected objects thanks to polarimetry and accurate distance evaluation of the obstacles (and hence their level of danger) via the disparity map. The use of non-conventional imaging provides an alternative to existing detection techniques by proposing the detection of surface-based properties rather than relying on gray levels or on the geometric properties of obstacles, as conventional scalar methods do. The ICUB project brings together two research laboratories (LITIS, LE2I) and two industrial partners (STEREOLABS and PSA). Each partner is eager to leverage polarimetric information to address road scene analysis.