Smooth-Trajectron++: Augmenting the Trajectron++ behaviour prediction model with smooth attention

Understanding traffic participants’ behaviour is crucial for predicting their future trajectories, enabling autonomous vehicles to better assess the environment and consequently anticipate possible dangerous situations at an early stage. While the integration of cognitive processes and machine learning models has demonstrated promise in various...

Are you sure? Modelling the Confidence of a Driver in Left-Turn Gap Acceptance Decisions

When a person makes a decision, it is automatically accompanied by a subjective probability judgement of the decision being correct, in other words, a (local) confidence judgement. Confidence judgements have, among other things, an<br/>effect on justifications of future decisions and behaviour. A better understanding of the metacognitive...

The relation between humans’ interactive behavior and fixation behavior in a coupled virtual reality driving simulator

In order to design safe and effective interactions between autonomous vehicles (AVs) and human road users, it is essential to understand the mechanisms underlying human-human merging behavior. Driving simulator experiments can be used to study these mechanisms, but previous research has primarily focused on the behavior of individual drivers...

Modeling embodiment during the rubber hand illusion: A dynamical model validated by a time-varied experiment

A common method to investigate multisensory integration is using multisensory illusions. The rubber hand illusion is one of the best-known multisensory illusion used in clinical applications. By stroking a visible rubber hand and the participant’s occluded hand, the illusion arises that the rubber hand belongs to the participant. Possible...

Significance of Static Backgrounds for Video Object Detection

Video Object Detectors (VID) are used in various applications such as surveillance, inspection, etc. Often in these applications there exists a spatial area of interest and a static background. The static backgrounds remain constant throughout the video sequence in the training data establishing an undesirable correlation with the moving object...

Analysing the Relation Between Gaze Location and Gap Acceptance Decisions During Highway Merges

Background: Merging on a highway is a complex driving task that requires a lot of interaction with other road users. During these tasks, a driver is required to evaluate gaps in space and time between the themselves and other road users and obstacles in order to arrive at the right moment to merge onto the highway. To improve safety and increase...

Analyzing the relation between the gap acceptance behavior and the response time of drivers' decisions during overtaking

Overtaking on two-lane roads can cause dangerous situations, due to drivers’ errors during the gap acceptance decision. Understanding gap acceptance decisions can help mitigate these situations. Response time (i.e. the time it takes the driver to evaluate the gap and make a decision) has been shown to provide valuable insights into the cognitive...

Aligning AI with Human Norms: Multi-Objective Deep Reinforcement Learning with Active Preference Elicitation

The field of deep reinforcement learning has seen major successes recently, achieving superhuman performance in discrete games such as Go and the Atari domain, as well as astounding results in continuous robot locomotion tasks. However, the correct specification of human intentions in a reward function is highly challenging, which is why state...

Dissipating phantom traffic jams with haptic shared control for longitudinal vehicle motion

Traffic jams occurring on highways cause increased travel time as well as increased fuel consumption and crashes. Traffic jams without a clear cause, such as an on-ramp or an accident, are called phantom traffic jams and are said to make up 50% of all traffic jams. They are the result of an unstable traffic flow caused by human driving behaviour...

The Effect of Prior Knowledge on Sense of Agency: Using Expectation-Maximization to Reproduce the Moving Rubber-Hand Illusion

When humans make inferences that go beyond limited, noisy, or ambiguous input data, background knowledge is necessary to make generalizations. Such inferences are important for designing intelligent artificial agents. Bayesian inference, a statistical method commonly used as a cognitive model of the brain, formalizes the integration of...