Survey on Safety and Efficiency in Automotive Embedded Systems
Keywords:
Adaptive systems, Automotive engineering, Embedded systems, Model predictive control, Multicore processing, Real-time systems, Safety enhancementAbstract
This survey article provides a comprehensive overview of recent advancements in automobile embedded systems, with a special focus on technologies that enhance vehicle safety, improve real-time computational capabilities, and optimize system performance through adaptive multicore platforms and model predictive control (MPC) structures. As modern vehicles become increasingly reliant on electronic control units (ECUs) and software-driven functionalities, the demand for efficient, scalable, and reliable embedded architectures has surged. The article examines the integration of adaptive multicore systems, which enable parallel processing and dynamic resource allocation, thereby improving the performance of embedded automotive applications. These systems are crucial in managing the complex and compute-intensive tasks associated with autonomous driving, advanced driver-assistance systems (ADAS), and in-vehicle infotainment. Real-time computation is another critical area discussed, as latency-sensitive operations such as collision avoidance, lane keeping, and emergency braking depend on precise timing and rapid response. To provide a deeper understanding of ongoing research, the article examines four significant contributions that address current limitations in embedded automotive systems. These studies highlight innovative approaches to mitigating timing unpredictability, enhancing fault tolerance, and improving energy efficiency. Additionally, model predictive control (MPC) structures are evaluated for their ability to handle multivariable control problems and constraints in real-time, which is essential for robust vehicle dynamics control and fuel efficiency.
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