Scenario Generation for Autonomous Vehicle Simulation Testing
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Solution Overview
Problem
Current simulation environments for testing autonomous vehicles lack the ability to efficiently generate diverse and realistic scenarios that reflect real-world conditions, making it difficult to effectively test the behavior of autonomous vehicles in all possible driving scenarios.
Innovation Solution
A computer-implemented method and system for generating scenarios in a simulation environment, which includes rendering a static scene topology, editing nodes for user input to define interactions between an ego object and challenger objects, and storing these interactions to create a scenario that can be executed on the static scene topology, allowing for the simulation of various interactions such as cut-in, cut-out, and follow lane behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical world testing is used to test autonomous vehicle behavior, then test reliability and realism are improved, but testing becomes expensive and time-consuming
Solution Approach 1:
The patent creates virtual copies of real-world driving scenarios through simulation environments. These simulated scenarios replicate physical world conditions including road layouts, weather conditions, traffic patterns, and actor behaviors, allowing comprehensive testing without physical deployment. The system generates multiple scenario variations by modifying parameters of base scenarios, enabling extensive testing coverage at fraction of the cost and time of physical testing.
2Productivity
If simulation environments are used to test autonomous vehicle behavior, then testing efficiency and cost are improved, but scenario realism and diversity may be reduced
Solution Approach 1:
The patent implements dynamic scenario generation where simulation parameters, environmental conditions, and actor behaviors are randomly varied within realistic ranges. The system dynamically adjusts scenario complexity, weather conditions, traffic density, and actor response patterns to create diverse yet realistic test cases. This dynamic approach ensures scenarios remain both computationally efficient for rapid testing and sufficiently realistic to validate autonomous vehicle performance.
Solution Approach 2:
The system modifies key scenario parameters such as weather conditions, road types, traffic patterns, and actor behaviors to generate diverse test scenarios from base templates. By systematically varying these parameters within realistic bounds, the system creates numerous scenario variations that maintain realism while enabling comprehensive testing coverage across different driving conditions without requiring proportional increases in physical testing resources.
3Reliability
If comprehensive scenario coverage is achieved in simulation, then testing completeness is improved, but scenario generation complexity increases
Solution Approach 1:
The patent segments scenario generation into modular components: base scenario templates, environmental parameters, actor behavior models, and interaction rules. Each component can be independently configured and combined to create comprehensive test scenarios. This modular segmentation allows the system to achieve thorough scenario coverage by systematically varying and combining discrete elements rather than managing monolithic complex scenario definitions, reducing overall system complexity while maintaining testing completeness.
Data Source
AI summary
A computer implemented method of generating a scenario to be run in a simulation environment for testing the behaviour of an autonomous vehicle includes rendering, on a display of a computer device, an image of a static scene topology; and rendering on the display an object editing node comprising a set of input fields for receiving user input. The object editing node is for parameterizing an interaction of a challenger object relative to an ego object; and the method includes receiving into the input fields of the object editing node user input defining at least one temporal or relational constraint of the challenger object relative to the ego object. The at least one temporal or relational constraints define an interaction point of a defined interaction stage between the ego object and the challenger object. The method includes storing the set of constraints and defined interaction stage in an interaction container in a computer memory of the computer system; and generating a scenario to be run in a simulation environment, the scenario comprising the defined interaction stage executed on the static scene topology at the interaction point.