This paper presents an innovative approach for the verification of truck platooning functions in complex automotive sensor topologies. Truck platooning provides a promising business case for truck automation to increase road capacity and reduce fuel consumption. It has therefore been instrumental in the ongoing innovation of Cooperative Adaptive Cruise Control (CACC), which paves the way for autonomous driving in the trucking industry. The scenario-based framework can benchmark the performance of truck platooning at the electronic system level using a Cluster-Hardware-in-the-Loop (Cluster-HiL) co-simulation platform. We demonstrate a systematic synthesis process for evaluating the functionality of truck platoons using three criticality indicators, such as required brake acceleration, Brake Threat Number (BTN) and Time-to-Brake (TTB). The proposed framework aims to bridge the gap between knowledge- and data-driven approaches to enable continuous extensibility of knowledge.