Joe Steinhauer

I2Connect focuses on developing next generation of Advanced Driver Assistance Systems (ADAS) for trucks. The emphasis will be on developing algorithms for fusion and situation assessment and prediction based on Evidence Theory, as well as adaptive human-machine interfaces (HMI).

The driver's ability to understand a current traffic situation, and anticipate future maneuvers of other traffic participants are key safety enablers. How can we help drivers observe the traffic safety of different traffic situations via information and warnings via a safety system?

This project aims to identify, adjust and implement AI methods to improve and create a more resilient drinking water production and distribution, where the operators at the drinking water plants are supported in their decision making processes.

Intention recognition is the task of inferring an agent´s intention based on its previous actions. It is crucial for human social intelligence which in turn enables understanding of, and for the ability to predict, other humans´ behaviours, such as for example other drivers´ intent to overtake, stop, turn, or switch lanes. For making situation-based decisions, both autonomous and human drivers need to take the intentions of surrounding vehicles into account. This is especially true in a mix of autonomous and human drivers.

Big data has gained much interesting in recent years due to the rapid expansion of the massive amount of data that is available for solving different types of tasks within many different application domains. However, today's big data is still on a fairly low level of abstraction when it comes to complex decision support tasks, subject to e.g. high dimensionality and significant portions of uncertainty regarding which patterns to look for in the data.

The HELICOPTER proposal aim at exploiting ambient-assisted living techniques to provide older adults (end users) and their informal caregivers with support, motivation and guidance in pursuing a healthy and safe lifestyle.