Simulation Clock Timing Alignment for Distributed Vehicle Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Distributed processing systems in vehicles face challenges in simulating realistic timing due to non-deterministic behavior, leading to variations in message timestamps and sequences across different executions, which can result in unrealistic event sequences and troubleshooting difficulties.
Innovation Solution
The system employs a simulation clock that remains static during processing tasks, using metadata from real-world scenarios to align frame initiation times and message timestamps, and introduces a statistical mode to account for latency and jitter, ensuring more realistic simulations through aligned and statistical timing modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a continuous simulation clock is used to advance time, then the simulation can progress through events, but the timing becomes non-deterministic and unrealistic due to processing variations
Solution Approach 1:
The simulation clock is segmented into discrete frames rather than continuous advancement. Each frame represents a specific time interval and is processed in order, ensuring deterministic timing while allowing flexible event scheduling within each frame. This segmentation resolves the non-deterministic behavior by establishing clear temporal boundaries for processing.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing timing metadata from real-world scenarios before simulation. This metadata includes observed execution times and message timestamps that are used to align simulation frames with real-world timing characteristics, ensuring realistic and deterministic simulation behavior without requiring continuous clock advancement.
2Manufacturing precision
If the simulation clock advances continuously, then time passes realistically, but message timestamps become variable and unrealistic across executions
Solution Approach 1:
The system changes the timing parameters by using observed execution times and message timestamps from real-world scenarios as metadata inputs. These parameters are stored and reused in simulations to maintain consistent, realistic timing characteristics. By anchoring simulation timestamps to real-world observed values rather than continuous clock advancement, timestamp consistency across executions is achieved.
Solution Approach 2:
The system copies timing characteristics from real-world scenario executions into the simulation environment. Metadata including observed execution times and message timestamps are extracted from real scenarios and used to replicate the same timing behavior in simulations. This copying ensures that message timestamps remain consistent and realistic across multiple simulation executions.
3Adaptability or versatility
If processing tasks execute with variable timing, then the system handles real-world variability, but simulation timing alignment becomes difficult
Solution Approach 1:
The system performs preliminary measurement of actual execution times and message timestamps during real-world scenario recording. This metadata is stored before simulation, allowing precise timing alignment during simulation by referencing the pre-measured values. This preliminary action enables the system to maintain timing flexibility in real-world operation while achieving precise timing alignment in simulation.
Solution Approach 2:
The system uses feedback from real-world timing measurements to adjust and align simulation timing. Observed execution times and message timestamps from actual operations are fed back into the simulation process to synchronize virtual clock events with real-world timing characteristics. This feedback mechanism enables accurate timing alignment while preserving the adaptability to handle real-world variability.
Data Source
AI summary
Systems and methods are provided for the accurate reproduction during simulation of distributed systems, such as vehicle-based processing systems. In a simulation, the execution times of individual tasks are aligned to those of a recorded process. Data consumed during the recorded process is also consumed during the corresponding portion of the simulation, and data generated during the simulation is associated with timing data from data generated during the recorded processes.