About
One of the main goals of our workshop is to bridge the gap between Computational Cognitive & Behavior Science, Explainable AI, Transportation, and the Autonomous Driving community. Our SIAM workshop mainly targets theoretical frameworks and practical algorithms of perception, decision-making, and planning integrated with social factors and computational cognitive science to enable autonomous vehicles (AVs) to interact with human agents in a socially compatible way. Specifically, the topics are as follows, but not limited to:
- Applications of AVs interacting with human agents;
- Algorithms of perception, decision-making, planning for human-like AVs;
- Cognitive aspects and models for autonomous driving;
- Cognitive and mental modeling toward socially driving, e.g., Theory of Mind and Theory of Machine;
- Social cues for AVs in interactive driving tasks;
- Action-reaction cycle modeling and validation;
- Explainable interaction and planning in interactive driving tasks;
- Evaluation and quantification of inter-human interactions and their implementations to human-AV interactions;
- Human driving behavior/intention modeling, simulation, and analysis;
- Heterogeneous human-agent teams;
- Interactive traffic scenes analysis;
- Interaction pattern learning, extraction, and recognition;
- Interactive simulations and humans-in-the-loop simulations;
- Learning-based theory for social interaction among human drivers;
- Social and group intelligence in multiple human agent interaction;
- Spatiotemporal driving behaviors in interactive traffic scenes;
