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Collaborating Authors

 Monte Carlo


Simulation to Reality: Testbeds and Architectures for Connected and Automated Vehicles

Klüner, David, Schäfer, Simon, Hegerath, Lucas, Xu, Jianye, Kahle, Julius, Ibrahim, Hazem, Kampmann, Alexandru, Alrifaee, Bassam

arXiv.org Artificial Intelligence

Ensuring the safe and efficient operation of CAVs relies heavily on the software framework used. A software framework needs to ensure real-time properties, reliable communication, and efficient resource utilization. Furthermore, a software framework needs to enable seamless transition between testing stages, from simulation to small-scale to full-scale experiments. In this paper, we survey prominent software frameworks used for in-vehicle and inter-vehicle communication in CAVs. We analyze these frameworks regarding opportunities and challenges, such as their real-time properties and transitioning capabilities. Additionally, we delve into the tooling requirements necessary for addressing the associated challenges. We illustrate the practical implications of these challenges through case studies focusing on critical areas such as perception, motion planning, and control. Furthermore, we identify research gaps in the field, highlighting areas where further investigation is needed to advance the development and deployment of safe and efficient CAV systems.


Believable Robot Characters

Simmons, Reid (Carnegie Mellon University) | Makatchev, Maxim (Carnegie Mellon University) | Kirby, Rachel (Carnegie Mellon University) | Lee, Min Kyung (Carnegie Mellon University) | Fanaswala, Imran (Carnegie Mellon University in Qatar) | Browning, Brett (Carnegie Mellon University) | Forlizzi, Jodi (Carnegie Mellon University) | Sakr, Majd (Carnegie Mellon University in Qatar)

AI Magazine

Believability of characters has been an objective in literature, theater, film, and animation. We argue that believable robot characters are important in human-robot interaction, as well. In particular, we contend that believable characters evoke users’ social responses that, for some tasks, lead to more natural interactions and are associated with improved task performance. In a dialogue-capable robot, a key to such believability is the integration of a consistent storyline, verbal and nonverbal behaviors, and sociocultural context. We describe our work in this area and present empirical results from three robot receptionist testbeds that operate "in the wild."