RSS Safety Test Scenarios With Real-Time Kinematics Rating
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Solution Overview
Problem
Existing simulation testbeds for autonomous driving systems lack RSS-specific test cases and working condition parameters, making it challenging to evaluate compliance with Responsibility-Sensitive Safety (RSS) standards, which are crucial for ensuring vehicle safety during autonomous operations.
Innovation Solution
Proposed RSS-specific test cases and working condition parameters are calculated backward from RSS formulas, and additional functional modules such as an RSS-specific real-time kinematics (RTK) status checker and an RSS-based rating module are introduced to enhance conventional simulation test systems, enabling accurate verification of RSS compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional simulation testbeds are used for autonomous driving systems, then general simulation capabilities are provided, but RSS-specific safety compliance evaluation is not achieved
Solution Approach 1:
The testbed is divided into distinct functional modules: scenario generation module, simulation execution module, RTK status checking module, and rating module. Each module handles a specific aspect of RSS compliance testing, making the complex evaluation process manageable and modular.
Solution Approach 2:
An RTK (Real-Time Kinematics) status checker is introduced as an intermediary component between the simulation execution and the rating module. This intermediary validates the kinematic status of vehicles in real-time during simulation, ensuring accurate RSS compliance evaluation without requiring direct modification of the core simulation engine.
2Measurement precision
If RSS-specific test cases and parameters are implemented, then RSS compliance evaluation accuracy is improved, but test system complexity increases
Solution Approach 1:
RSS-specific test cases and working condition parameters are pre-calculated using RSS formulas before simulation execution. This preliminary preparation ensures that all necessary test scenarios and parameters are ready in advance, enabling precise RSS compliance evaluation without requiring complex real-time calculations during simulation.
Solution Approach 2:
The system dynamically adjusts and monitors key parameters such as longitudinal distance, lateral distance, response time, and braking acceleration during simulation. By focusing on these specific RSS-defined parameters, the system achieves precise compliance evaluation while managing complexity through parameter specialization.
3Reliability
If additional functional modules are added to enhance conventional test systems, then RSS compliance verification capability is improved, but system complexity increases
Solution Approach 1:
The rating module is designed to perform multiple functions: it evaluates RTK status, assesses RSS compliance, and generates comprehensive test results. This multi-functional approach enhances RSS compliance verification capability while avoiding the need for separate dedicated modules for each evaluation task.
Solution Approach 2:
The system implements continuous feedback loops where the RTK status checker monitors simulation states in real-time, validates kinematic parameters, and provides feedback to the rating module. This feedback mechanism ensures accurate RSS compliance verification without requiring overly complex system architecture.
Data Source
AI summary
System and techniques for test verification of a control system (e.g., a vehicle safety system) with a vehicle operation safety model (VOSM) such as Responsibility Sensitive Safety (RSS) are described. In an example, using test scenarios to measure performance of VOSM includes: defining safety condition parameters of a VOSM for use in a test scenario configured to test performance of a safety system; generating a test scenario, using the safety condition parameters, the test scenario generated as a steady state test, a dynamic test, or a stress test; executing the test scenario with a test simulator, to produce test results for the safety system; measuring real-time kinematics of the safety system, during execution of the test scenario, based on compliance with the safety condition parameters; and producing a parameter rating for performance of the safety system with the VOSM, based on the test results and the measured real-time kinematics.