Prof. Dr. Falk Uebernickel

OSRAM Case 2017/18

Challenge: "How might we design innovative exterior automotive lighting solutions in the context of fully automated driving for road users considering the structure of the value chain in the automotive industry?. 
As highly and fully autonomous vehicles are expected to represent over two thirds of all new cars sold in 2030, the automotive industry and consequently everyday traffic will undergo a massive transformation within the next decade. Requirements of future cars concepts and design as well as the demands of future traffic behaviour, interaction and communication will change accordingly. With autonomous vehicles conquering the streets, humans are no longer the only ones in the driver’s seat, causing diverse consequences."

IRIS represents an innovative solution solving the problem of human road users that do not understand the intentions of autonomous vehicles. Autonomous vehicles lack the possibility of eye-contact-communication with the driver as there is no human being steering the car. Thus, road users have a feeling of insecurity and distrust. As current autonomous vehicle concepts and designs are not taking this aspect into consideration, the intentions of an autonomous vehicle stay hidden and are not recognizable for other road users so far. Allowing road users to interpret and understand the autonomous vehicles’ intentions with the help of IRIS, enables them to better analyze the current traffic and to adapt their behavior accordingly. IRIS enables pedestrians and other traffic participants to perceive and understand the intentions of autonomous vehicles intuitively by creating a way to communicate between humans and machines. This makes self-driving vehicles appear predictable and hence creates trust. 

IRIS consists of a multitude of individually controllable LEDs, installed in a line-like shape across the car´s body on the front, rear and on each side from front to rear, ensures high visibility from all perspectives while allowing the autonomous vehicle to display various light-patterns according to the traffic scenario. 
In the case of an autonomous vehicle stopping for a pedestrian who wants to cross a street, IRIS reduces the number of LEDs glowing in a downward movement as well as the luminosity of the light stripes according to the velocity of the vehicle. This supports the pedestrians’ perception of the car slowing down in an intuitive manner by addressing his/ her subconscious perception of the moving object. 
Thanks to the innovative concept of using cross-cultural functioning, subconsciously perceivable light patterns, autonomous vehicles do not need to issue commands to road users. They only communicate their own behavioral actions and intentions, hence minimizing possible misunderstandings. Accordingly, messages do not have to address road users personally in order to be valid. In contrast to communicating commands, communicating behavioral intentions furthermore avoids possible liability risks in case of an accident caused by an autonomous vehicle.
In an interdisciplinary team of seven students from the University of St. Gallen namely Felix Meindl, Marc Nesch and Severin Kranz, as well as the Technical University of Munich including Anja Holzgethan, Benedikt Specht, Chunchien Chang and Fabian Schäfer the previously introduced challenge of the corporate partner Osram has been tackled within the time span of ten months. Within seven design sprints, the project team developed 32 prototypes that have been tested with more than 160 users. The final prototype IRIS was additionally validated both qualitatively and quantitatively by more than 380 users within 6 testing cycles and scientific online experiment with road users from all over the world.