Context: Collaborative systems enable multiple independent systems to work together towards a common goal. These systems can include both human-system and system-system interactions and can be found in a variety of settings, including smart manufacturing, smart transportation, and healthcare. Safety is an important consideration for collaborative systems because one system's failure can significantly impact the overall system performance and adversely affect other systems, humans or the environment. Goal: Fail-safe mechanisms for safety-critical systems are designed to bring the system to a safe state in case of a failure in the sensors or actuators. However, a collaborative safety-critical system must do better and be safe-operational, for e.g., a failure of one of the members in a platoon of vehicles in the middle of a highway is not acceptable. Thus, failures must be compensated, and compliance with safety constraints must be ensured even under faults or failures of constituent systems. Method: In this paper, we model and analyze safety for collaborative safety-critical systems using hierarchical Coloured Petri nets (CPN). We used an automated Human Rescue Robot System (HRRS) as a case study, modeled it using hierarchical CPN, and injected some specified failures to check and confirm the safe behavior in case of unexpected scenarios. Results: The system behavior was observed after injecting three types of failures in constituent systems, and then safety mechanisms were applied to mitigate the effect of these failures. After applying safety mechanisms, the HRRS system's overall behavior was again observed both in terms of verification and validation, and the simulated results show that all the identified failures were mitigated and HRRS completed its mission. Conclusion: It was found that the approach based on formal methods (CPN modeling) can be used for the safety analysis, modeling, validation, and verification of collaborative safety-critical systems like HRRS. The hierarchical CPN provides a rigorous way of modeling to implement complex collaborative systems.