Connected and automated vehicles can be seen as a revolution in the global automotive industry, bringing a new mobility paradigm and having a huge impact on several economic sectors such as logistics industry. Significant progress has been made in the field of autonomous truck driving with numerous prototypes. However, challenges need to be addressed in order to ensure the uptake of this breakthrough technology and the future advent of an overall autonomous logistic chain. The deployment of autonomous heavy-duty vehicles is hindered by the current inabilities of these vehicles to work with the right safety and functional level for 24/7 availability (e.g. harsh weather conditions) and by the lack of harmonized regulatory framework. This project aims at developing and enabling to deploy a safe autonomous transportation systems in a wide range of real-life use cases in a variety of different scenarios. This encompasses the development of autonomous driving system (ADS) capable of handling adverse environmental conditions such as heavy rain, snowfall, fog. The ADS solution will be based on multiple sensor modalities to address 24/7 availability. The ADS will then be integrated into multiple vehicle types used in low-speed areas. Finally, these vehicles will be deployed, integrated and operated in a variety of real-life use cases to validate their value in the application and identify any limitations: forklift (un)loading in warehouses and industrial plants, hub-to-hub shuttle service on open road, automated baggage dispatching in airports, container transfer operations and vessel loading in ports. Logistics operations will be optimized thanks to a new fleet management system that will act as a control tower, gathering all information from subsystems (vehicles, road sensors, etc.) to coordinate the operations and protect vulnerable road users. This work should then enable commercial exploitation of the technology and policy recommendations for certifications processes.

SafeNcy project aims at designing, developing, testing and validating a TRL5 on-board function for the FMS capable to support the pilot in the decision making process following an emergency situation with degraded and adverse conditions. Firstly, an emergency landing site selection algorithm will be developed, using a database of possible landing sites that is constantly updated via data-link connection with the airline Operating Control Centre (OCC) and which takes into account updated meteorological information and potential hazards. This landing site will minimize also the collateral effect of the emergency landing by selecting landing sites with a minimum population density and low risk propagation. Secondly, an on-board trajectory generation prototype will be developed in order to compute the best emergency trajectory from the aircraft to the selected landing site(s). This algorithm will also take into account the most up-to-date meteorological information, consider the degraded dynamics of the aircraft resulting from some failures, and will have a robust design allowing real-time capabilities. Finally, a thorough verification and validation campaign will be performed, developing an ad-hoc simulator for testing purposes and integrating it with a fault detection and identification external block provided by the Topic Leader. The consortium has been structured to gather and organise complementary expertise and capabilities to answer the project objectives. It is formed by two SMEs, CGX AERO (coordinator) and Metsafe; DSNA Services, the expertise and consultancy office of the French civil aviation; two universities, ENAC and UPC; and Eurocontrol, all supported by an internal advisory board composed of active pilots from large and low-cost airline, Aviation, Accident and Investigation, Human Factors and ATM experts, from the French Civil Aviation Authority, and Military pilots, human factors and flight dynamics experts from the French Air Force Academy.