Distributed Cyber-Physical Systems are often safety-critical and, therefore, establishing their safety is of paramount importance. High-level models like timed graph transformation systems have been developed to cover the complex context-aware and self-aware behavior formally and enable to often verify safety at this level. To cover the communication delays inherent in Distributed Cyber-Physical Systems, also adding delay-robustness to these models has been studied. However, ensuring safety by design is often in conflict with other relevant goals like, for example, high throughput, as oftentimes the need for a delay-robust design leads to an overcautious behavior. By incorporating planning-awareness into the design such that Distributed Cyber-Physical Systems agents share their planning information, one can avoid the need to sacrifice throughput to ensure safety, compared to a design that is limited to context and self-awareness alone. In this paper, we develop an approach employing timed graph transformation systems for Distributed Cyber-Physical Systems (i) to model planning-awareness without compromising verifiability, (ii) to derive such a model systematically from a non-planning-aware model, and (iii) to analyze for the derived model whether it compromises throughput to establish safety less often than the employed non-planning-aware model. As a running example, we consider a Distributed Cyber-Physical Systems in which multiple autonomous shuttles locally coordinate their movement on a track topology to avoid collisions while maximizing throughput.