Same-Loop AV Simulation for Deterministic Driving Outputs
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Solution Overview
Problem
Existing autonomous driving systems face computational inconsistencies and inaccuracies due to separate development of sensors, perception, localization, and decision-making systems, leading to unpredictable behavior in real-world environments, as simulations often do not accurately reflect the actual environment conditions.
Innovation Solution
Implementing a same-loop adaptive simulation and computation method where the autonomous driving system processes simulations concurrently with real-world operations, using the same computational loop to ensure deterministic outputs and improve accuracy by simulating movements based on actual environment data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If separate development of sensors, perception, localization, and decision-making systems is used, then device complexity is reduced and ease of manufacture is improved, but computational inconsistencies and inaccuracies occur leading to unpredictable behavior
Solution Approach 1:
The patent merges separate development loops (sensor calibration, perception, localization, decision-making) into a unified same-loop adaptive simulation framework. All components are developed and tested together in an integrated computational environment, ensuring that computational inconsistencies between separately developed modules are eliminated while maintaining the benefits of modular development.
2Loss of time
If traditional simulation methods are used, then development time is reduced, but simulations do not accurately reflect actual environment conditions leading to inaccuracies
Solution Approach 1:
The system implements feedback mechanisms where simulation results are continuously compared with real-world sensor data and environmental conditions. The same-loop adaptive simulation uses actual environment data to adjust and refine simulation parameters in real-time, ensuring that simulations accurately reflect actual conditions while maintaining efficient development cycles.
Solution Approach 2:
The patent applies preliminary action by pre-configuring the simulation environment with actual environmental data and conditions before testing begins. The system prepares adaptive simulation scenarios in advance using real-world parameters, ensuring that when simulations run, they already reflect accurate environmental conditions without requiring extensive post-processing or recalibration.
3Measurement precision
If concurrent simulation with real-world operations is implemented, then simulation accuracy is improved, but computational load and system complexity increase
Solution Approach 1:
The patent segments the concurrent simulation system into distinct functional modules: data acquisition module, simulation execution module, comparison module, and adaptation module. Each module handles specific tasks independently, reducing overall system complexity while enabling accurate concurrent simulation. The segmentation allows parallel processing of different computational tasks without creating bottlenecks.
Data Source
AI summary
A method may include obtaining, by an autonomous driving system, input information relating to an autonomous vehicle (AV). The method may include determining, by the autonomous driving system, one or more driving signals that describe operations of the AV. The method may include instructing the AV to move according to the driving signals and simulating, by a virtual driving system, movement of the AV based on the driving signals, wherein the simulating the movement of the AV occurs concurrently with the AV moving according to the driving signals as instructed.