All weather autonomous real logistics operations and demonstrations
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.