Generalized Inequality-based Approach for Probabilistic WCET Estimation

Estimating the probabilistic Worst-Case Execution Time (pWCET) is essential for ensuring the timing correctness of real-time applications, such as in robot IoT systems and autonomous driving systems. While methods based on Extreme Value Theory (EVT) can provide tight bounds, they suffer from model uncertainty due to the need to decide where the upper tail of the distribution begins. Conversely, inequality-based approaches avoid this issue but can yield pessimistic results for heavy-tailed distributions. This paper proposes a method to reduce such pessimism by incorporating saturating functions (arctangent and hyperbolic tangent) into Chebyshev's inequality, which mitigates the influence of large outliers while preserving mathematical soundness. Evaluations on synthetic and real-world data from the Autoware autonomous driving stack demonstrate that the proposed method achieves safe and tighter bounds for such distributions.

D-AWSIM: Distributed Autonomous Driving Simulator for Dynamic Map Generation Framework

Autonomous driving systems have achieved significant advances, and full autonomy within defined operational design domains near practical deployment. Expanding these domains requires addressing safety assurance under diverse conditions. Information sharing through vehicle-to-vehicle and vehicle-to-infrastructure communication, enabled by a Dynamic Map platform built from vehicle and roadside sensor data, offers a promising solution. Real-world experiments with numerous infrastructure sensors incur high costs and regulatory challenges. Conventional single-host simulators lack the capacity for large-scale urban traffic scenarios. This paper proposes D-AWSIM, a distributed simulator that partitions its workload across multiple machines to support the simulation of extensive sensor deployment and dense traffic environments. A Dynamic Map generation framework on D-AWSIM enables researchers to explore information-sharing strategies without relying on physical testbeds. The evaluation shows that D-AWSIM increases throughput for vehicle count and LiDAR sensor processing substantially compared to a single-machine setup. Integration with Autoware demonstrates applicability for autonomous driving research.

Work in Progress: Middleware-Transparent Callback Enforcement in Commoditized Component-Oriented Real-time Systems

Real-time scheduling in commoditized component-oriented real-time systems, such as ROS 2 systems on Linux, has been studied under nested scheduling: OS thread scheduling and middleware layer scheduling (e.g., ROS 2 Executor). However, by establishing a persistent one-to-one correspondence between callbacks and OS threads, we can ignore the middleware layer and directly apply OS scheduling parameters (e.g., scheduling policy, priority, and affinity) to individual callbacks. We propose a middleware model that enables this idea and implements CallbackIsolatedExecutor as a novel ROS 2 Executor. We demonstrate that the costs (user-kernel switches, context switches, and memory usage) of CallbackIsolatedExecutor remain lower than those of the MultiThreadedExecutor, regardless of the number of callbacks. Additionally, the cost of CallbackIsolatedExecutor relative to SingleThreadedExecutor stays within a fixed ratio (1.4x for inter-process and 5x for intra-process communication). Future ROS 2 real-time scheduling research can avoid nested scheduling, ignoring the existence of the middleware layer.