No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

Driver behavior models have been used as input to self-coaching, accident prevention
studies, and developing driver-assisting systems. In recent years, driver behavior …

A major challenge to deploying robots widely is navigation in human-populated
environments, commonly referred to as social robot navigation. While the field of social …

Despite their tremendous success in many applications, large language models often fall
short of consistent reasoning and planning in various (language, embodied, and social) …

Interaction‐aware autonomous driving (IAAD) is a rapidly growing field of research that
focuses on the development of autonomous vehicles (AVs) that are capable of interacting …

Given the popular presupposition of human reasoning as the standard for learning and
decision making, there have been significant efforts and a growing trend in research to …

Autonomous vehicles currently suffer from a time-inefficient driving style caused by
uncertainty about human behavior in traffic interactions. Accurate and reliable prediction …

When developing AI systems that interact with humans, it is essential to design both a
system that can understand humans, and a system that humans can understand. Most deep …

Theory of Mind (ToM), the ability to understand people's minds, is an essential ingredient for
developing machines with human-level social intelligence. Recent machine learning …

Studies have shown that autonomous vehicles (AVs) behave conservatively in a traffic
environment composed of human drivers and do not adapt to local conditions and socio …