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Identification of evasive manoeuvres in traffic interactions and conflicts

The study presents a simple and easy to implement method for detection of the evasive action start in traffic interactions. The method is based on comparison of the studied trajectory with a reference set of ‘unhindered’ trajectories, interpreting the start of evasive action as the moment when no more similarities can be found. The suggested algorithm performs well for primary interactions when ro

Interact or counteract? Behavioural observation of interactions between vulnerable road users and autonomous shuttles in Oslo, Norway

The current paper presents the results of behavioural observations in a field experiment with automated shuttles in Oslo, Norway. Video observations were conducted at five fixed locations along a challenging 1.2 km automated shuttle line with varying traffic conditions. Observed interactions between vulnerable road users and automated shuttles were coded using a predefined codebook, which allowed

Learning-Based Controller Design with Application to a Chiller Process

In this thesis, we present and study a few approaches for constructing controllers for uncertain systems, using a combination of classical control theory and modern machine learning methods. The thesis can be divided into two subtopics. The first, which is the focus of the first two papers, is dual control. The second, which is the focus of the third and last paper, is multiple-input multiple-outp