MotionWise Introduces Data-Driven Scheduling Feature

The MotionWise Schedule tool, developed by TTTech Auto, plays a crucial role in managing bounded end-to-end latencies for scheduling software tasks and communication in automotive networks where safety and real-time behavior are paramount.

TTTech Auto has recently integrated dataflow driven scheduling support into the MotionWise scheduler, enabling the handling of dataflow dependencies and facilitating dynamic switching between different dataflows. This scheduling model is based on Directed Acyclic Graphs (DAG) with parallel execution on multiple CPU cores, ensuring efficient and straightforward modeling of computation chains.

With the ability to enforce end-to-end latency bounds across multiple CPU cores in system on chip devices, MotionWise Schedule supports various industry standards such as AUTOSAR, POSIX, Data Distribution Service (DDS), and Time Sensitive Networking (TSN).

As the automotive industry transitions towards software-defined vehicles (SDVs), characterized by a growing number of software components, intricate dependencies, and complex hardware resources, the need for advanced scheduling tools has become more pressing. TTTech Auto, as part of the NXP ecosystem for SDV software, is at the forefront of addressing these challenges.

Ensuring consistent end-to-end timing from sensors to actuators has become increasingly critical, especially with the limitations of traditional testing methodologies. The complexity of allocating software components to resources while maintaining system integrity under varying loads necessitates innovative solutions.

The MotionWise Schedule tool, leveraging TTech Auto’s scheduling algorithms, adopts a correct-by-design approach to map software components and communication to hardware resources effectively. Dr. Stefan Poledna, CTO and Co-Founder of TTTech Auto, emphasizes the importance of achieving safety and real-time behavior through this approach.

Building on the success of the MotionWise safety middleware, MotionWise Schedule has already been deployed in over 2 million vehicles, with a promising pipeline of more than 9 million vehicles in the near future.

In software-defined vehicle projects, manual scheduler configuration often leads to prolonged testing cycles and delays in production timelines. MotionWise Schedule addresses this challenge by offering workload separation based on criticality, task dependency scheduling, and robust failure handling mechanisms.

By implementing these functionalities within the vehicle’s embedded stack, MotionWise Schedule significantly reduces the time required for software releases, encompassing design, testing, and validation phases. This runtime environment ensures safe execution, real-time scheduling, end-to-end timing guarantees, and other critical properties.

As the first modular solution in the MotionWise family, MotionWise Schedule encapsulates cutting-edge technology in a flexible product that seamlessly integrates with standardized and custom architectures. It optimizes resource utilization and performance through task and network communication scheduling, promoting a correct-by-design approach.

Time-Triggered execution in MotionWise Schedule provides time-boxed isolation between tasks, enabling mix-criticality scenarios and enhancing determinism and execution repeatability. This approach reduces testing efforts for real-time tasks and accelerates system integration.

Task monitoring features offer comprehensive insights into task performance and sequencing, facilitating real-time analysis and system-level optimization. Time synchronization across multiple SoCs and Ethernet TSN ensures minimized latency and supports real-time performance analysis.

Intuitive tooling in MotionWise Schedule allows for visualizing schedules and comparing plans with actual execution, enabling quick identification of resource issues and supporting efficient system-level optimizations.

By abstracting software functionality from hardware, MotionWise Schedule streamlines the scheduling process and supports mixed-criticality systems with minimal re-validation efforts for incremental updates.

For more information, visit www.tttech-auto.com.