Sensing & Sensibility

As digital transformation continues, everyday technologies will fundamentally change: they will become proactive, autonomous and more and more opaque for humans. 

This research project examines how cooperation between humans and algorithmic agents can and ought to be designed, with regard to three potentially competing objectives: performance, satisfaction and accountability. Different types of human-algorithm-cooperation examples were created followed by exploring their impact on the efficiency and effectiveness of the result, the work satisfaction and wellbeing of the humans involved and societal and regulatory implications. 

The project furthermore addresses broader issues of how to design human-algorithm-cooperation between the priorities of industry, workers, and society at large.


Master Thesis

“Do You Want to Drive Together?” - A Use Case Analysis on Cooperative, Automated Driving.

Bhavana Malve

Driving automation aims to enhance comfort, safety, and traffic flow by removing the human driver from the control loop. However, the human experience of commuting involves more than just reaching a destination or assuming the role of a driver. Factors like route selection, driving style, and courtesy towards fellow road users are integral to the driving experience but often overlooked in automated vehicle design.

This thesis explores the desires of passengers in highly automated cars to participate in vehicle control. A video vignette study (N=16) was initiated to understand users’ needs for cooperation. Consequently, a Human-Machine Interface for cooperative control was developed and evaluated in a VR simulation study (N=15). Results indicate that most participants expressed a desire for cooperative driving, albeit varying with the driving situation. Moreover, allowing cooperation improved passengers’ overall experience by satisfying psychological needs for autonomy, security, competence, and relatedness.