Hybrid Log Driving Simulation for Realistic Agent Trajectories
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Solution Overview
Problem
Creating realistic driving simulations that accurately reflect real-world scenarios is challenging due to the difficulty in replicating the behavior of simulated agents, which often deviate from their real-world counterparts.
Innovation Solution
The use of hybrid log-based simulations, where log data from real-world vehicle operations is used to instantiate simulated vehicles and environments, allowing for the recreation of real-world scenarios and behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional simulated agents are used in driving simulations, then the simulation can be executed, but the simulated agents exhibit behavior that deviates from real-world counterparts, reducing realism
Solution Approach 1:
The patent uses recorded log data from real-world vehicles as templates to create simulated agents, copying actual driving behaviors, trajectories, and environmental interactions directly from real data rather than relying on synthetic behavior models. This ensures simulated agents exhibit authentic real-world behavior patterns
Solution Approach 2:
The system pre-processes and records real-world driving log data before simulations, creating a library of authentic behavioral templates that can be directly applied during simulation execution. This preliminary capture of real behavior eliminates the need for complex real-time behavior generation algorithms
2Reliability
If real-world scenarios are tested directly, then authentic behavior can be observed, but safety concerns and practical limitations prevent testing of dangerous scenarios
Solution Approach 1:
The patent introduces a simulated environment as an intermediary between real-world data and testing objectives. Real log data is instantiated within a virtual simulation framework, allowing dangerous or rare scenarios to be reproduced and tested without exposing physical vehicles or personnel to actual risks
Solution Approach 2:
Dangerous real-world scenarios are copied into the simulation environment using recorded log data, enabling repeated testing of hazardous situations (e.g., emergency braking, pedestrian crossings) without real-world safety risks while maintaining behavioral authenticity
3Adaptability or versatility
If simulated environments are created from scratch, then customization is possible, but the behavior deviates from real-world scenarios
Solution Approach 1:
The patent applies different qualities to different aspects of the simulation: real recorded behavior data is used for agent trajectories and interactions (high fidelity), while the environmental framework and scenario structure can be customized (flexibility). This local differentiation maintains realism where it matters while allowing scenario adaptability
Data Source
AI summary
Techniques for determining a response of a simulated vehicle to a simulated object in a simulation are discussed herein. Log data captured by a physical vehicle in an environment can be received. Object data representing an object in the log data can be used to instantiate a simulated object in a simulation to determine a response of a simulated vehicle to the simulated object. Additionally, one or more trajectory segments in a trajectory library representing the log data can be determined and instantiated as a trajectory of the simulated object in order to increase the accuracy and realism of the simulation.