New deep learning & big data frameworks application to simultaneous classification, segmentation and pose detection for future self-driving cars
Our project assumes that the launch of automated vehicles on public roads will only be successful if a user centric approach is used where the technical aspects go hand in hand in compliance with societal values, user acceptance, behavioural intentions, road safety, social, economic, legal and ethical considerations.
The research proposed line aims to enhance the flight control systems onboard of unmanned aerial systems (drones) to develop new intelligent technological capabilities that meet with the most ambitious requirements reagarding smaart cities (energy saving and efficiency in specific societal services). Thanks to the innovative technique CACM-RL developed by SOTICOL RS, drones can perform optimal missions considering optimal criteria, such as, energy minimum consumption or minimum time. In addition, by using this technique, drones can perform special missions in a swarm configuration, if ncessary.
Energy management plays a vital role in maintaining sustainability and reliability of smart grids. It also helps to prevent blackouts. Energy management at consumer’s side is a complex task. It requires efficient scheduling of appliances with minimum delay to reduce peak to average ratio and energy consumption cost. Classification of appliances is based on their energy consumption pattern. Bio-inspired optimization algorithms can be used to efficiently schedule the energy management and help in the reduction on the energy consumption.
Driver Assistance Systems (ADAS) have spread within the automotive industry, supporting the driver e.g. for braking, steering or automated systems like adaptive cruise control, automatic emergency braking or lane keeping assist. However, for automation level 3, these sub-functions require further developments concerning user acceptance to facilitate their adoption. The main goal of EPIC proposal is to contribute to the adoption of automated vehicles by considering the needs and requirements of all the road users (drivers and VRUs), assuring safe and acceptable integration of key