Poster: Cloud-Based Passenger Safety Monitoring for Agentic Autonomous Public Transport

This work studies continuous cloud-based passenger-safety monitoring for autonomous public transport using vision-language models. Nine anomalous situations were staged inside an autonomous shuttle and recorded from three camera angles. The evaluation examines recognition quality and end-to-end latency across several video configurations, identifying upload latency and video quality as key networking factors for timely agentic responses.