Advanced STCO for Next-Gen Automotive Systems

This paper explores the development of electronic solutions for automotive applications, focusing on chiplet-based systems as means to balance performance and cost particularly in advanced driver assistance systems (ADAS). As a key function in modern vehicles, ADAS technologies including adaptive cruise control, lane-keeping assistance, and automatic emergency braking - rely on a wide array of sensors, cameras, and radar to enhance vehicle safety and the driving experience. These systems require substantial computational power for real-time data processing, sensor fusion, and machine learning. Consequently, packaging solutions must meet stringent demands for thermal management, reliability, miniaturization, and compliance with automotive safety standards. A major industry trend is the shift toward centralized and edge computing architectures. Central compute units aggregate data from various sensors for complex decisionmaking, while edge nodes execute time-critical tasks locally to minimize latency. Both architectures benefit from chiplet-based designs, which offer modularity, scalability, and costeffectiveness by enabling the reuse and customization of compute components across multiple subsystems. This paper evaluates several integration technologies suitable for chipletbased ADAS platforms, including silicon interposers, advanced organic substrates, glass interposers, and embedded bridges. The advantages and trade-offs of each approach are analyzed with respect to performance, cost, and reliability targets specific to the automotive domain.