127 citations · 188 across the 10 of their papers we have counts for
10 papers
Linking Behaviour and Perception to Evaluate Meaningful Human Control over Partially Automated Driving
Ashwin George, Lucas Elbert Suryana, Lorenzo Flipse +5
Partial driving automation creates a tension: drivers remain legally responsible while being less active in control. Meaningful human control (MHC), a normative framework that can…
Using Feasible Action-Space Reduction by Groups to fill Causal Responsibility Gaps in Spatial Interactions
Ashwin George, Vassil Guenov, Arkady Zgonnikov +2
Heralding the advent of autonomous vehicles and mobile robots that interact with humans, responsibility in spatial interaction is burgeoning as a research topic. Even though metric…
Can a mobile robot learn from a pedestrian model to prevent the sidewalk salsa?
Olger Siebinga, David Abbink
Pedestrians approaching each other on a sidewalk sometimes end up in an awkward interaction known as the "sidewalk salsa": they both (repeatedly) deviate to the same side to avoid…
Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions
Ashwin George, Luciano Cavalcante Siebert, David A. Abbink +1
Understanding the causal influence of one agent on another agent is crucial for safely deploying artificially intelligent systems such as automated vehicles and mobile robots into…
A merging interaction model explains human drivers' behaviour from input signals to decisions
Olger Siebinga, Arkady Zgonnikov, David Abbink
One of the bottlenecks of automated driving technologies is safe and socially acceptable interactions with human-driven vehicles, for example during merging. Driver models that pro…
Merging in a Coupled Driving Simulator: How do drivers resolve conflicts?
Olger Siebinga, Arkady Zgonnikov, David A. Abbink
Traffic interactions between merging and highway vehicles are a major topic of research, yielding many empirical studies and models of driver behaviour. Most of these studies on me…
Feasible Action-Space Reduction as a Metric of Causal Responsibility in Multi-Agent Spatial Interactions
Ashwin George, Luciano Cavalcante Siebert, David Abbink +1
Modelling causal responsibility in multi-agent spatial interactions is crucial for safety and efficiency of interactions of humans with autonomous agents. However, current formal m…
A model of communication-enabled traffic interactions
O. Siebinga, A. Zgonnikov, D. A. Abbink
A major challenge for autonomous vehicles is handling interactive scenarios, such as highway merging, with human-driven vehicles. A better understanding of human interactive behavi…
Uncovering variability in human driving behavior through automatic extraction of similar traffic scenes from large naturalistic datasets
Olger Siebinga, Arkady Zgonnikov, David Abbink
Recently, multiple naturalistic traffic datasets of human-driven trajectories have been published (e.g., highD, NGSim, and pNEUMA). These datasets have been used in studies that in…
Meaningful human control: actionable properties for AI system development
Luciano Cavalcante Siebert, Maria Luce Lupetti, Evgeni Aizenberg +10
How can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits -…