The TARANTO project targets to break the technological barriers to the development of the next BiCMOS technology platforms, allowing the improvement of the performance of the HBT (Heterojunction Bipolar Transistors) with a much higher level of integration. This new generation of transistors HBT will be a key factor to meet the needs of high-speed communications systems and high data rate required for the integration of heterogeneous intelligent systems as well as for intelligent mobility systems that will be used in future fully automated transport systems. The main objectives of this project will be to develop transistors HBT offering high maximum frequency (Fmax: 600GHz) built to very high density CMOS processes: 130 / 90nm for IFX, 55 / 28nm to ST, while IHP will work on the project to achieve maximum frequencies of 700GHz remaining compatible with IFX and ST BiCMOS processes. The project consortium gathers the main European players in the value chain for these applications at very high frequencies, from laboratories to industrial users, thus ensuring the highest scientific level and the ability to validate the work carried out on appropriate demonstrators.

The ambition of PRYSTINE is to strengthen and to extend traditional core competencies of the European industry, research and universities in smart mobility and in particular the electronic component and systems and cyber-physical systems domains. PRYSTINE's target is to realize Fail-operational Urban Surround perceptION (FUSION) which is based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. Therefore, PRYSTINE's high-level goals are: 1. Enhanced reliability and performance, reduced cost and power of FUSION components 2. Dependable embedded control by co-integration of signal processing and AI approaches for FUSION 3. Optimized E/E architecture enabling FUSION-based automated vehicles 4. Fail-operational systems for urban and rural environments based on FUSION PRYSTINE will deliver (a) fail-operational sensor-fusion framework on component level, (b) dependable embedded E/E architectures, and (c) safety compliant integration of Artificial Intelligence (AI) approaches for object recognition, scene understanding, and decision making within automotive applications. The resulting reference FUSION hardware/software architectures and reliable components for autonomous systems will be validated in in 22 industrial demonstrators, such as: 1. Fail-operational autonomous driving platform 2. An electrical and highly automated commercial truck equipped with new FUSION components (such as LiDAR, Radar, camera systems, safety controllers) for advanced perception 3. Highly connected passenger car anticipating traffic situations 4. Sensor fusion in human-machine interfaces for fail-operational control transition in highly automated vehicles PRYSTINE’s well-balanced, value chain oriented consortium, is composed of 60 project partners from 14 different European and non-European countries, including leading automotive OEMs, semiconductor companies, technology partners, and research institutes.

The vision of TINKER is to provide a new cost- and resource efficient pathway for RADAR and LIDAR sensor package fabrication with high throughput up to 250units/min, improved automation by 20%, improved accuracy by 50% and reliability by a factor of 100 to the European automotive and microelectronic industry via additive manufacturing and inline feedback control mechanisms. Autonomous driving and self-driving cars represent one prominent example for the use of microelectronics and sensor, most importantly RADAR and LIDAR sensors. Their respective markets have a big potential, e.g. it is estimated that the market size of LIDAR in automotive will double itself in the next two years (within 2020 to 2022). The public awareness and the industrial need for further miniaturization of such sensor packages is the main driver of ongoing efforts in the automotive sector to be able to integrate such devices into the car body like in the bumps and head lamps instead of attaching them (e.g. on top of the car in case of LIDAR device). Safety (for the driver and others) is the most important key aspect of the automotive sector. Therefore highly-value and high performance RADAR and LIDAR systems are required for advanced driver-assistance systems (ADAS) as well as robotic cars. Current bottlenecks are relevantly large size of such sensor devices, their weight and power consumption. Since these factors are highly limited within cars, further miniaturization and improving functionality and efficient use of resources is highly demanded.