In this paper, we present a general methodology to estimate safety related parameter values of cooperative cyber-physical system-ofsystems. As a case study, we consider a vehicle platoon model equipped with a novel distributed protocol for coordinated emergency braking. The estimation methodology is based on learning-based testing; which is an approach to automated requirements testing that combines machine learning with model checking. Our methodology takes into account vehicle dynamics, control algorithm design, inter-vehicle communication protocols and environmental factors such as message packet loss rates. Empirical measurements from road testing of vehicle-to-vehicle communication in a platoon are modeled and used in our case study. We demonstrate that the minimum global time headway for our platoon model equipped with the CEBP function scales well with respect to platoon size.
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